DETAILED ACTION
This is a Final Office action is in response to communications filed on March 26th, 2026. Claim 1 and 9-10 is amended and new claim 11 is added. Claims 1-11 have been examined in this application.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more.
Step 1: Claims 1-8 is/are drawn to system (i.e., a manufacture), claims 9 is/are drawn to method (i.e., a process), and claims 10 is/are drawn to computer readable storage media (i.e., a manufacture). (Step 1: YES).
Step 2A - Prong One: In prong one of step 2A, the claim(s) is/are analyzed to evaluate whether it/they recite(s) a judicial exception.
Claim 1: A search device, comprising:
one or more processors, wherein at least one of the processors acquires a search string,
the search string being entered by a user into an entry field,
determines whether the acquired search string contains a tag based on tag information from a server,
deletes the tag from the search string,
and sets the tag as a search index, when determining that the search string contains the tag,
generates, based on the set search index and a remaining character string,
search information for searching targeted information,
the remaining character string being made by deleting the tag from the search string,
and acquires a search result based on the generated search information,
wherein when the processor deletes the tag from the search string and sets the tag as the search index, the processor causes the display of information indicating completion of setting of the tag as the search index so as to allow the user to visually recognize the information.
(Examiner notes: The underlined claim terms above are interpreted as additional elements beyond the abstract idea and are further analyzed under Step 2A - Prong Two)
Under their broadest reasonable interpretation, the independent claims is/are directed to the abstract idea of receiving a user-entered search string, identifying a tag/category within the search string, separating/removing the tag from the remaining query text, using the tag as a search criterion/index, generating search information using the tag and remaining text, obtaining search results, and displaying information indicating that the tag/search criterion has been set. This corresponds to methods of organizing human activity and mental process, such as categorizing information i.e. characterized as organizing, analyzing, and displaying information, filtering content based on labels, and searching within a selected category, activities because the core operations of recognizing a label/category in text, separating that label from remaining text, treating the label as a search criterion, and displaying the resulting applied criterion are acts that can be performed conceptually by a human using observation, judgment, and pen and paper, which the courts have repeatedly held to be abstract ideas. See Alice Corp. v. CLS Bank Int’l, 573 U.S. 208 (2014); Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016). Thus, the claimed subject matter is directed to an abstract idea falling within the judicial exception category of “mental processes” and “certain methods of organizing human activity”. From applicant’s specification, the claimed invention is implemented to “an accommodation facility may be provided with a review containing a sentence “This is not a non-smoking facility.” The reviewed accommodation facility, which is actually a cigar-friendly facility, may be unintentionally retrieved as a search result of the searching based on only the entry field containing the character string “near a mall, non-smoking” as in this embodiment. In addition, the user does not always voluntarily select the tag “non-smoking”. In order to solve these problems, this embodiment is characterized by automatic deletion of the character string corresponding to the tag from the search string and selection of the tag even in the case of the searching based on only the entry field” (see 0037 of instant specification). The claims recite a mental process, namely analyzing a user’s search input, identifying a predefined tag, separating the tag from remaining text, and using the tag to guide a search, which can be performed by a human using basic judgment and rules without the aid of a computer. Further the claims also recite a method of organizing human activity, specifically categorizing and filtering information using predefined labels to retrieve desired content, which is a fundamental information management practice (i.e. including analyzing search input, categorizing information using predefined tags, and retrieving information based on those categories). The Examiner notes that although the claim limitations are summarized, the analysis regarding subject matter eligibility considers the entirety of the claim and all of the claim elements individually, as a whole, and in ordered combination.
And the dependent claims 2-8 and 11 recites an abstract idea, merely recites timing of tag removal, user interactions, displaying visual indications, and autocomplete behavior, which merely describe conventional user-interface operations and presentation of information. These additional limitations do not alter the fundamental character of the claims, which remains focused on the abstract concept of parsing a query, categorizing it using predefined rules, and retrieving information accordingly. Accordingly, the claims are directed to an abstract idea under 35 U.S.C. §101, namely data organization, classification, and information retrieval based on rules applied to user input, rather than to an improvement in computer technology itself. As such, the claims are directed to an abstract idea involving certain methods of organizing human activity and mental processes, which falls within a judicial exception under 35 U.S.C. §101.
Independent claim(s) 9 and 10 recite/describe nearly identical steps (and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and this/these claim(s) is/are therefore determined to recite an abstract idea under the same analysis.
As such, the Examiner concludes that claims 1 recites an abstract idea (Step 2A – Prong One: YES).
Step 2A - Prong Two: In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional elements, that integrate the exception into a practical application of that exception. An “addition element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception.
The requirement to execute the claimed steps/functions using a search device, processors, computer, server, etc. (Claims 1, 9, and 10) is/are equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer.
Similarly, the limitations of using a search device, processors, computer, server, etc. (Claims 1, 19, and 10, and dependent claims 2-8 and 11) are recited at a high level of generality and amount to no more than mere instructions to apply the exception using generic computer components. This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(f)).
Further, the additional limitations beyond the abstract idea identified above, serves merely to generally link the use of the judicial exception to a particular technological environment or field of use. Specifically, it/they serve(s) to limit the application of the abstract idea to computerized environments (e.g., acquire, determine, delete, generate, index, etc. steps performed by a search device, processors, computer, etc.). This reasoning was demonstrated in Intellectual Ventures I LLC v. Capital One Bank (Fed. Cir. 2015), where the court determined "an abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer"). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application (see MPEP 2106.05(h)).
The recited additional element(s) of steps of acquiring a search string (the search string being entered by a user into an entry field), determining whether the acquired search string contains a tag based on tag information from a server, deleting the tag from the search string, setting the tag as a search index, generating search information based on the set search index and a remaining character string (the remaining character string being made by deleting the tag from the search string), acquiring a search result based on the generated search information, and causing display of information indicating completion of setting of the tag as the search index so as to allow the user to visually recognize the information merely describe data gathering, data recognition/classification, data manipulation, search execution, and output/display of results, which are ancillary to the underlying abstract idea of categorizing and searching information based on predefined rules. Likewise, the recited computer operations simply apply the abstract idea using generic computing components to collect, process, and display information, which constitutes insignificant extra-solution activity without adding any technical improvement (Independent Claims 1, 9, and 10), additionally and/or alternatively simply append insignificant extra-solution activity to the judicial exception, (e.g., mere pre-solution activity, such as data gathering, in conjunction with an abstract idea). This/these limitation(s) do/does not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. (See MPEP 2106.05(g)).
Dependent claims 2-8 and 11 fail to include any additional elements. In other words, each of the limitations/elements recited in respective dependent claims is/are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e., they are part of the abstract idea recited in each respective claim).
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (Step 2A – Prong two: NO).
Step 2B: In step 2B, the claims are analyzed to determine whether any additional element, or combination of additional elements, is/are sufficient to ensure that the claims amount to significantly more than the judicial exception. This analysis is also termed a search for an "inventive concept." An "inventive concept" is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself. Alice Corp., 134 S. Ct. at 2355, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966).
As discussed above in “Step 2A – Prong 2”, the identified additional elements in independent Claims 1, 9, and 10, and dependent claims 2-8 and 11 are equivalent to adding the words “apply it” on a generic computer, and/or generally link the use of the judicial exception to a particular technological environment or field of use. Therefore, the claims as a whole do not amount to significantly more than the judicial exception itself.
The recited additional element(s) of acquiring a search string, deleting a tag from the search string, setting the tag as a search index, generating search information, and acquiring a search result merely describe data gathering, data manipulation, and output of results, which are ancillary to the underlying abstract idea of categorizing and searching information based on predefined rules (Independent Claims 1, 9, and 10), additionally and/or alternatively simply append insignificant extra-solution activity to the judicial exception, (e.g., mere pre-solution activity, such as data gathering, in conjunction with an abstract idea), i.e. these steps merely describe collect, process, and display information, which is similar to “Receiving or transmitting data over a network, e.g., using the Internet to gather data”, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), “Storing and retrieving information in memory”, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; “Presenting offers to potential customers and gathering statistics generated based on the testing about how potential customers responded to the offers; the statistics are then used to calculate an optimized price”, OIP Technologies, 788 F.3d at 1363, 115 USPQ2d at 1092-93, Determining an estimated outcome and setting a price, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93, is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here) (See MPEP 2106.05(d) (II)).
This conclusion is based on a factual determination. Applicant’s own disclosure at paragraph [0041] acknowledges that “when the user selects one of these candidate words, Step S15 is executed involving determination of whether the input search string contains the character string identical to any of the tags indicated by the tag information 112. Specifically, just after entry of a character string “near a mall, non”, candidate words, such as “non-smoking” and “non-acceptance”, may be displayed, as illustrated in FIG. 10. The selection of a candidate word “non-smoking” may lead to execution of Steps S15 to S18 illustrated in FIG. 4, followed by a jump to the display screen illustrated in FIG. 7. This modification can achieve setting of a tag during entry of a search string, and therefore simplify the user’s manipulation”. The recited additional elements — including a processor, an entry field, tag information from a server, a search index, search information, a search result, and display of information to a user — are recited at a high level of generality and perform their ordinary functions of receiving data, processing data, searching data, and displaying data. The amended limitations of determining whether a search string contains a tag, deleting the tag from the search string, setting the tag as a search index, and generating search information based on the tag/search index and remaining character string merely describe generic data analysis and data manipulation. The limitation of displaying information indicating completion of setting or deletion merely presents the result of the information processing to the user. This additional element therefore do not ensure the claim amounts to significantly more than the abstract idea.
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer or/and append the abstract idea with insignificant extra solution activity associated with the implementation of the judicial exception, (e.g., mere data gathering, post-solution activity) and/or simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
The dependent claims 2-8 and 11 fail to include any additional elements. In other words, each of the limitations/elements recited in respective independent claims is/are further part of the abstract idea as identified by the Examiner for each respective dependent claim (i.e., they are part of the abstract idea recited in each respective claim).
Specifically, performing tag deletion at the time of a search manipulation (Claim 2) or during query entry (Claim 3) reflects a routine timing choice for executing known query-processing steps. Triggering tag deletion and index setting in response to a user manipulation (Claim 4) is a conventional way of allowing user-controlled filtering. Restricting search results to those matching remaining text within an indexed category (Claim 5) reflects ordinary Boolean or faceted searching. Displaying visual indications of tag deletion or index setting (Claims 6 and 7) and providing complemented character strings with tag handling upon selection (Claim 8), and deleting the tag at a timing of selection of a complemented character string displayed while the user is entering the search string (claim 11). These limitations do not introduce any new technical functionality or improvement to computer technology, but instead describe conventional control logic, user interaction, and display operations that are routinely implemented in generic search systems and therefore fail to integrate the abstract concept into a practical application and it is recited at a high level of generality and does not integrate the judicial exception into a practical application.
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claim(s) amount to significantly more than the abstract idea identified above (Step 2B: NO).
Therefore, claims 1-11 are not eligible subject matter under 35 USC 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status:
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 4-7, and 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Pub. 20150169582 (“Jain”) in view U.S. Pat. 9298816 (“Dimassimo”) in view U.S. Pat. 12169499 (“Cannon”).
As per claims 1, 9, and 10, Jain discloses, one or more processors, wherein at least one of the processors (Examiner interprets a computerized query processing system including processors and computing devices configured to process queries and return results) (“a query processing system 100 according to one illustrative embodiment. Query processing system 100 includes a query processor 110, a matching engine 120, a ranking engine 130 and a knowledge base database 140. It should be noted that the components of the query processing system 100 in some embodiments may reside on a single computing device while in other embodiments some or all of the components may reside on multiple different computing devices connected to each other such that they can work in cooperation with each other. In a distributed environment any one of the components of FIG. 1 may be distributed from any of the other components. Further, in the distributed environment the components may be present on different servers or virtual machines, where each of the different servers or virtual machines may execute one or more of the functions of the components”) (0025, 0072-0075) acquires a search string (Examiner interprets that the Jain’s query processor 110 receives input query 101 and converts the received query into a format that permits matching against documents stored in an enhanced index or other index in knowledge base 140. Jain further discloses that query 101 may be directly input by a user by typing a question into a search box) (“Query processor 110 is configured to receive the input query 101 and convert the received query into a format that permits the query to be matched against documents stored in an enhanced index or other type of index in the knowledge base 140. Query 101 typically is a query that is directly input to the system 100 by a user by for example typing in a question into a search box. However, query 101 can include system data and operations data such as software configuration data typically represented as a list of key, value pairs, settings, alerts, events, diagnostics logs, error codes, performance data, configuration snapshots or any other data that may be reported out from a computing system. In order to ensure an accurate match of documents in the knowledge base 140 the query processor 110, in one illustrative embodiment, includes three components, a query analysis module 112, a query fuzzing module 114 and a query distributor module 116. In some embodiments the query processor 110 includes a cache 111 that holds in a cache previously received queries and results that may be returned in the event that the query matches a previous query”) (0026),
the search string being entered by a user into an entry field (Examiner interprets that the query 101 is directly input by a user, for example by typing a question into a search box. The Examiner interprets the disclosed search box as corresponding to the claimed entry field) (“Query 101 typically is a query that is directly input to the system 100 by a user by for example typing in a question into a search box. However, query 101 can include system data and operations data such as software configuration data typically represented as a list of key, value pairs, settings, alerts, events, diagnostics logs, error codes, performance data, configuration snapshots or any other data that may be reported out from a computing system. In order to ensure an accurate match of documents in the knowledge base 140 the query processor 110, in one illustrative embodiment, includes three components, a query analysis module 112, a query fuzzing module 114 and a query distributor module 116. In some embodiments the query processor 110 includes a cache 111 that holds in a cache previously received queries and results that may be returned in the event that the query matches a previous query”) (0026),
determines whether the acquired search string contains a tag based on tag information from a server (Examiner interprets that the named-entity filter 240 identifies named entities in the query. For example, Jain recognizes that “SQL Server” is a named entity rather than two unrelated words, and modifies token-order information so that “SQL Server” is identified as a single token rather than two separate tokens. Jain further discloses that “SQL Server” and “logical processors” may be tagged as “Software Entity” in an ontology model. The Examiner interprets the identified named entity / ontology tag as corresponding to the claimed tag) (“Named entity filter 240 is a filter that is configured to identify named-entities in the query. For example if the document states "Install SQL Server on your machine." It becomes helpful to identify and recognize that "SQL Server" is a named entity and not two separate unrelated words. The named entity filter 240 modifies the token order information of the query so that the words "SQL Server" are identified as a single token and not as two separate tokens … named entity filter 240 obtains a list of named entities from a domain expert where the named entities have been mapped to an ontology model to identify other features that are common to the named entities. For example "SQL Server" and "logical processors" may be tagged as "Software Entity" in the ontology model. This list of named entities may also be created automatically or automatically in conjunction with a domain expert … builds a graph as a pre-processing step to enable fast lookups. In this graph, nodes denote words and edges connect words if they occur together in a phrase in the named-entity list”) (0036-0039) based on tag information from a server (Examiner interprets that the named-entity filter obtains a list of named entities mapped to an ontology model to identify features common to the named entities. The Examiner interprets the ontology/entity information used by the named-entity filter as corresponding to tag information) (“The named entity filter 240 obtains a list of named entities from a domain expert where the named entities have been mapped to an ontology model to identify other features that are common to the named entities. For example "SQL Server" and "logical processors" may be tagged as "Software Entity" in the ontology model. This list of named entities may also be created automatically or automatically in conjunction with a domain expert”) (0037, 0024-0026),
deletes the tag from the search string (Examiner interprets the query processor “adds, removes or modifies terms from the query.” Jain also discloses a truncation level including a stop-word filter, where filters may reduce the overall size of the query by removing or combining tokens in the query. Jain further discloses that stop-word filter 250 removes words from query 101, and that terms common to the subject matter of the knowledge base may also be removed to reduce noise. The Examiner interprets these disclosures as teaching removal of query tokens from the search string) (“FIG. 2B is a block diagram illustrating an organization of the filters 210-290 according to a secondary approach to the application of the filters to the query according to one illustrative embodiment. At the first level 201 the query is tokenized using the tokenizer 210. At the next level 202 is the canonicalization of the query. At level 202 filters 220, 230 and 240 are grouped. However it should be noted that other types of filters which provide canonicalization may also be present at this level. At level 203 is the truncation of the query. Level 203 includes the stop word filter 250.”) (0030, 0035, 0006)
and sets the tag as a search index (Examiner interprets that the query processor converts the received query into a modified query compatible with an enhanced index or other index in the knowledge base, and uses named-entity recognition and query analysis to identify terms for use in the modified query. Jain’s query analysis module rewrites the query, substitutes value-type terms, processes the input query using filters, and generates terms used for querying the knowledge base) (“Query analysis module 112 is configured to prepare an abstract representation of the query. It does this by rewriting the query and substituting any value-types it finds (e.g., numbers like 7 or seven, Boolean words like true or false) with generics (e.g., NUMERIC and BOOLEAN, respectively) and stores the value separately for constraint evaluation by the Matching Engine 120. Query analysis module 112 is further configured to mimic the processing that happens on the input corpus during the index building phase … FIG. 2 shows the various filters that process the input query. Depending on how the documents are indexed in the knowledge base 140 the input query may not pass through the expansion phase as synonyms may instead have been added to the index during the index building stage. It should be noted that various embodiments of the present disclosure may have different filters present and not all of the filters are required. A developer has the ability to pick and choose which of the filters illustrated in FIG. 2A are applicable or usable by the query processing system 100”) (0026-0030, 0036-0040), when determining that the search string contains the tag (Examiner interprets that the Named-entity filter identifies related terms/entities inside the query string and recognizes them as a single semantic entity/tag) (“Named entity filter 240 is a filter that is configured to identify named-entities in the query. For example if the document states "Install SQL Server on your machine." It becomes helpful to identify and recognize that "SQL Server" is a named entity and not two separate unrelated words. The named entity filter 240 modifies the token order information of the query so that the words "SQL Server" are identified as a single token and not as two separate tokens … named entity filter 240 obtains a list of named entities from a domain expert where the named entities have been mapped to an ontology model to identify other features that are common to the named entities. For example "SQL Server" and "logical processors" may be tagged as "Software Entity" in the ontology model. This list of named entities may also be created automatically or automatically in conjunction with a domain expert … builds a graph as a pre-processing step to enable fast lookups. In this graph, nodes denote words and edges connect words if they occur together in a phrase in the named-entity list”) (0036-0039),
generates, based on the set search index and a remaining character string, search information for searching targeted information (Examiner interprets query processor generates a modified query from the input query, and the matching engine uses the modified query to identify documents in the knowledge base. Jain also teaches tokenization, removal or combination of tokens, and approximate searching using subsets of terms from the input query. The Examiner interprets the modified query and remaining query terms as corresponding to the claimed generated search information and remaining character string) (“Query analysis module 112 is configured to prepare an abstract representation of the query. It does this by rewriting the query and substituting any value-types it finds (e.g., numbers like 7 or seven, Boolean words like true or false) with generics (e.g., NUMERIC and BOOLEAN, respectively) and stores the value separately for constraint evaluation by the Matching Engine 120. Query analysis module 112 is further configured to mimic the processing that happens on the input corpus during the index building phase … FIG. 2 shows the various filters that process the input query. Depending on how the documents are indexed in the knowledge base 140 the input query may not pass through the expansion phase as synonyms may instead have been added to the index during the index building stage. It should be noted that various embodiments of the present disclosure may have different filters present and not all of the filters are required. A developer has the ability to pick and choose which of the filters illustrated in FIG. 2A are applicable or usable by the query processing system 100”) (0027-0031, 0043-0049, 0060-0069),
the remaining character string being made by deleting the tag from the search string (Examiner interprets that the query analysis module applies a sequence of filters to the input query, including tokenization, canonicalization, truncation, expansion, and normalization. Jain further discloses that the truncation level includes stop-word filter 250, and that this filter removes words from query 101. Jain explains that words such as “a,” “an,” “and,” “the,” “is,” “are,” “my,” and “our” may be removed from the query, and that subject-matter-specific words may also be removed when they create noise rather than value. Thus, under the Examiner’s broadest reasonable interpretation, Jain teaches deleting a recognized token from the query string and leaving a remaining set of query terms, which corresponds to the claimed remaining character string made by deleting the tag from the search string) (“FIG. 2B is a block diagram illustrating an organization of the filters 210-290 according to a secondary approach to the application of the filters to the query according to one illustrative embodiment. At the first level 201 the query is tokenized using the tokenizer 210. At the next level 202 is the canonicalization of the query. At level 202 filters 220, 230 and 240 are grouped. However it should be noted that other types of filters which provide canonicalization may also be present at this level. At level 203 is the truncation of the query. Level 203 includes the stop word filter 250 … Stop word filter 250 is applied to the query 101 to remove frequently occurring common words in the natural language from the query. In one embodiment stop word filter 250 uses a list of the most frequently occurring words in the language which the documents have been indexed against. For example in English words such as "a" "an" "and" "the" "is" "are" "my" "our" etc. will be removed from the query. Additionally certain words that are common in the subject matter of the knowledge base may also be removed. This list of words could be provided to the system from a developer or organization that helps identify words that typically would not be removed, but because of the subject matter may create more noise than providing value to a person looking for the information”) (0030-0035),
and acquires a search result based on the generated search information (Examiner interprets the matching engine takes the modified query and identifies documents in the knowledge base that match the modified query, and the ranking engine ranks the documents in order of relevance) (“The matching engine 120 takes the modified query and proceeds to identify documents in the knowledge base 140 that match the terms in modified query. This is illustrated at step 330. The matching engine 120 may invoke one or more of the matchers … At step 440 the token extractor 122 identifies in the documents tokens that give meaning to the numeric values that caused the match to occur. The token extraction 122 further captures the actual value associated with the numeric indication in the index for the documents. The token extractor 122 may use logic to convert text in the documents into mathematical expressions or understandings that may assist in determining if the document is a true match or is actually relevant to the inputted query … Ranking engine 130 receives from the matching engine 120 the documents found in the knowledge base and ranks the documents in order of relevance. This is illustrated at step 340. The ranking engine may employ different ranking or scoring equations in determining how to rank a document that was retrieved. Different matching methods may be given higher or lower scores by the ranking engine 130”) (0043-0049, 0062-0069),
wherein when the processor deletes the tag from the search string and sets the tag as the search index (Examiner interprets that the query processor adds, removes, or modifies terms from the query and generates a modified version of the query by passing the query through filters. Jain further discloses tokenizing the query, applying truncation and stop-word filtering to remove terms from query 101, and using the remaining/modified query terms to query a knowledge base index. Jain also discloses named-entity recognition, where recognized terms such as “SQL Server” may be tagged as “Software Entity” in an ontology model. The Examiner interprets the removed or modified query token as corresponding to the claimed deleted tag, and interprets Jain’s conversion of query 101 into a modified query compatible with an enhanced index or other index in knowledge base 140 as corresponding to setting the recognized tag/query information as a search index) (“query processor adds, removes or modifies terms from the query. The query processor provides a broad range of functionalities. For instance, it can add or recognize that two words that appear to be separate words actually identify a specific software entity or it can determine that a number appearing in a query is not just a numeric value but that it refers to a specific version or a number relevant to the specific configuration problem”) (0006, 0026-0030, 0035-0037).
Jain discloses, removing or modifying terms/tokens from a query and generating a modified query based on remaining query terms, but specifically doesn’t disclose, display of information indicating completion of setting of the tag as the search index, however Dimassimo discloses, the processor causes the display of information indicating completion of setting of the tag as the search index (Examiner interprets the search interface displaying faceted search results, where each faceted search result includes user interface elements for including or excluding that faceted search result as a search term in a subsequent search, such as by using a filter query. Dimassimo discloses plus/minus buttons for including or excluding a faceted search result, and the user interface elements refine the search query and search results based on selected facets) (“Upon selection of the plus or minus signs, a new selection summary box may be displayed as shown in FIG. 5. This selection summary box provides the status of the refined search parameters, i.e. which elements are included and which are excluded. This refined search box may include a user interface element next to each search term to enable the user to deselect the search term. This may be a virtual button with an X, for example, as shown in the figure. The selection summary is updated each time a further selection is made to include or exclude a faceted search result as a search term”) (Col. 10 Ln. 20-30).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, display of information indicating completion of setting of the tag as the search index, as taught by Dimassimo for the purpose so that a user could visually recognize which recognized query terms, entities, or filters had been applied, thereby improving usability, transparency of query processing, and search-result accuracy.
Jain specifically doesn’t disclose, so as to allow the user to visually recognize the information, however Cannon discloses, so as to allow the user to visually recognize the information (Examiner interprets that a filter section is updated to indicate that a filter has been applied, and that the filter is shown as a filter token object enabling the user to select, modify, or remove the corresponding filter. Cannon further teaches that the filter token object may be generated to indicate that a filter or other processing is being applied, and may indicate additional query commands associated with a statement i.e. Cannon’s filter token object as further teaching display of information that visually indicates an applied search/filter condition to the user) (“the filter token object 1033 may be generated by the user interface system 502 and/or the semantic processing system 504 similar to the manner in which the model display objects are generated. In some cases, the filter token object 1033 is generated to indicate that a filter is being applied to the data from the statement 1010D that differs from filters applied to other statements 1010 (e.g., a different or custom time range is being used) and/or to indicate that a filter (or other processing) is being applied to the data in addition to whatever processing is to be done as a result of the corresponding statement 1010D. For example, the filter token object 1033 can indicate that an enriched data processing package will include additional query commands associated with the statement 1010D (or additional (search-related) statements) than what is shown in the data processing package 1009”) (Col. 73 Ln. 1-16, Col. 74 Ln. 17-35).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, so as to allow the user to visually recognize the information, as taught by Cannon for the purpose to use such a filter-token object in a query-processing interface to improve user understanding of active filters or refinements, improve transparency of the search process, and permit the user to select, modify, or remove active refinements.
As per claims 2, Jain discloses, wherein the processor acquires the search string, and deletes the tag from the search string at a timing of a searching manipulation performed by a user (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that the query processors adds, removes, or modifies terms from the query and removes terms through tokenization/truncation/stop-word filtering) (“query processor adds, removes or modifies terms from the query. The query processor provides a broad range of functionalities. For instance, it can add or recognize that two words that appear to be separate words actually identify a specific software entity or it can determine that a number appearing in a query is not just a numeric value but that it refers to a specific version or a number relevant to the specific configuration problem”) (0006, 0026-0030, 0035-0037).
Jain discloses, removing or modifying terms/tokens from a query and generating a modified query based on remaining query terms, but specifically doesn’t disclose, string at a timing of a searching manipulation performed by a user, however Dimassimo discloses, string at a timing of a searching manipulation performed by a user (Examiner interprets the search interface displaying faceted search results, where each faceted search result includes user interface elements for including or excluding that faceted search result as a search term in a subsequent search, such as by using a filter query. Dimassimo discloses plus/minus buttons for including or excluding a faceted search result, and the user interface elements refine the search query and search results based on selected facets) (“The user may click, touch or otherwise select any one of the faceted search results (e.g., the listed subjects, topics, names, etc. under each facet) to obtain content relevant to that particular subject, topic or name” and “Upon selection of the plus or minus signs, a new selection summary box may be displayed as shown in FIG. 5. This selection summary box provides the status of the refined search parameters, i.e. which elements are included and which are excluded. This refined search box may include a user interface element next to each search term to enable the user to deselect the search term. This may be a virtual button with an X, for example, as shown in the figure. The selection summary is updated each time a further selection is made to include or exclude a faceted search result as a search term”) (Col. 9 Ln. 20-30 and Col. 10 Ln. 1-30).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, display of information indicating completion of setting of the tag as the search index, as taught by Dimassimo for the purpose to perform Jain’s query-term processing in response to Dimassimo’s user search-manipulation event so that the user could control which recognized terms or filters are applied to refine the search, thereby improving usability, transparency, and search-result relevance.
As per claims 4, Jain discloses, wherein when the processor determines that the search string contains the tag, the processor deletes the tag from the search string, and sets the tag as the search index, in response to a manipulation for setting of the tag performed by a user (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that the detecting named entities/tags, removing/modifying query terms, and converting the query into index-compatible modified query information) (“Query analysis module 112 is configured to prepare an abstract representation of the query. It does this by rewriting the query and substituting any value-types it finds (e.g., numbers like 7 or seven, Boolean words like true or false) with generics (e.g., NUMERIC and BOOLEAN, respectively) and stores the value separately for constraint evaluation by the Matching Engine 120. Query analysis module 112 is further configured to mimic the processing that happens on the input corpus during the index building phase … FIG. 2 shows the various filters that process the input query. Depending on how the documents are indexed in the knowledge base 140 the input query may not pass through the expansion phase as synonyms may instead have been added to the index during the index building stage. It should be noted that various embodiments of the present disclosure may have different filters present and not all of the filters are required. A developer has the ability to pick and choose which of the filters illustrated in FIG. 2A are applicable or usable by the query processing system 100”) (0026-0030, 0036-0040).
Jain discloses, removing or modifying terms/tokens from a query and generating a modified query based on remaining query terms, but specifically doesn’t disclose, , in response to a manipulation for setting of the tag performed by a user, however Dimassimo discloses, in response to a manipulation for setting of the tag performed by a user (Examiner interprets the user selection of faceted search result by plus/minus icons to include or exclude a facet search as a later search term/filter query) (“The user may click, touch or otherwise select any one of the faceted search results (e.g., the listed subjects, topics, names, etc. under each facet) to obtain content relevant to that particular subject, topic or name” and “Upon selection of the plus or minus signs, a new selection summary box may be displayed as shown in FIG. 5. This selection summary box provides the status of the refined search parameters, i.e. which elements are included and which are excluded. This refined search box may include a user interface element next to each search term to enable the user to deselect the search term. This may be a virtual button with an X, for example, as shown in the figure. The selection summary is updated each time a further selection is made to include or exclude a faceted search result as a search term”) (Col. 9 Ln. 20-30 and Col. 10 Ln. 1-30).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, in response to a manipulation for setting of the tag performed by a user, as taught by Dimassimo for the purpose so that a user could visually recognize which recognized query terms, entities, or filters had been applied, thereby improving usability, transparency of query processing, and search-result accuracy.
As per claims 5, Jain discloses, wherein the search result is one or more pieces of the targeted information that correspond to the remaining character string, among pieces of the targeted information that belong to the search index contained in the search information (Examiner interprets the matching engine takes the modified query and identifies documents in the knowledge base that match the modified query, and the ranking engine ranks retrieved documents) (“The matching engine 120 takes the modified query and proceeds to identify documents in the knowledge base 140 that match the terms in modified query. This is illustrated at step 330. The matching engine 120 may invoke one or more of the matchers … At step 440 the token extractor 122 identifies in the documents tokens that give meaning to the numeric values that caused the match to occur. The token extraction 122 further captures the actual value associated with the numeric indication in the index for the documents. The token extractor 122 may use logic to convert text in the documents into mathematical expressions or understandings that may assist in determining if the document is a true match or is actually relevant to the inputted query … Ranking engine 130 receives from the matching engine 120 the documents found in the knowledge base and ranks the documents in order of relevance. This is illustrated at step 340. The ranking engine may employ different ranking or scoring equations in determining how to rank a document that was retrieved. Different matching methods may be given higher or lower scores by the ranking engine 130”) (0043-0049, 0062-0069).
As per claims 6, Jain discloses, wherein when the processor deletes the tag from the search string, the processor displays information indicating completion of deletion of the tag so as to allow a user to visually recognize the information (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that the query processors adds, removes, or modifies terms from the query and removes terms through tokenization/truncation/stop-word filtering) (“query processor adds, removes or modifies terms from the query. The query processor provides a broad range of functionalities. For instance, it can add or recognize that two words that appear to be separate words actually identify a specific software entity or it can determine that a number appearing in a query is not just a numeric value but that it refers to a specific version or a number relevant to the specific configuration problem”) (0006, 0026-0030, 0035-0037).
Jain specifically doesn’t disclose, so as to allow the user to visually recognize the information, however Cannon discloses, so as to allow the user to visually recognize the information (Examiner interprets that Cannon supplies visual-display teaching: a filter token object is generated to indicate that a filter or token processing is being applied and can visually represent applied processing/query commands i.e. the displayed filter token object as visually indicating that the deleted/converted tag has been processed as an applied filter or query command, and Cannon further teaches that the filter token object may be generated to indicate that a filter or other processing is being applied, and may indicate additional query commands associated with a statement) (“the filter token object 1033 may be generated by the user interface system 502 and/or the semantic processing system 504 similar to the manner in which the model display objects are generated. In some cases, the filter token object 1033 is generated to indicate that a filter is being applied to the data from the statement 1010D that differs from filters applied to other statements 1010 (e.g., a different or custom time range is being used) and/or to indicate that a filter (or other processing) is being applied to the data in addition to whatever processing is to be done as a result of the corresponding statement 1010D. For example, the filter token object 1033 can indicate that an enriched data processing package will include additional query commands associated with the statement 1010D (or additional (search-related) statements) than what is shown in the data processing package 1009”) (Col. 73 Ln. 1-16, Col. 74 Ln. 17-35).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, so as to allow the user to visually recognize the information, as taught by Cannon for the purpose to use such a filter-token object in a query-processing interface to improve user understanding of active filters or refinements, improve transparency of the search process, and permit the user to select, modify, or remove active refinements.
As per claims 7, Jain discloses, wherein when the processor deletes the tag from the search string and sets the tag as the search index (Examiner interprets that the query processor adds, removes, or modifies terms from the query and generates a modified version of the query by passing the query through filters. Jain further discloses tokenizing the query, applying truncation and stop-word filtering to remove terms from query 101, and using the remaining/modified query terms to query a knowledge base index. Jain also discloses named-entity recognition, where recognized terms such as “SQL Server” may be tagged as “Software Entity” in an ontology model. The Examiner interprets the removed or modified query token as corresponding to the claimed deleted tag, and interprets Jain’s conversion of query 101 into a modified query compatible with an enhanced index or other index in knowledge base 140 as corresponding to setting the recognized tag/query information as a search index) (“query processor adds, removes or modifies terms from the query. The query processor provides a broad range of functionalities. For instance, it can add or recognize that two words that appear to be separate words actually identify a specific software entity or it can determine that a number appearing in a query is not just a numeric value but that it refers to a specific version or a number relevant to the specific configuration problem”) (0006, 0026-0030, 0035-0037).
Jain discloses, removing or modifying terms/tokens from a query and generating a modified query based on remaining query terms, but specifically doesn’t disclose, display of information indicating completion of setting of the tag as the search index, however Dimassimo discloses, the processor displays information indicating completion of setting of the tag as the search index so as to allow a user to visually recognize the information (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that upon selection of plus/minus signs, a new selection summary box is displayed, providing the status of refinement search parameters, including which elements are included/excluded) (“Upon selection of the plus or minus signs, a new selection summary box may be displayed as shown in FIG. 5. This selection summary box provides the status of the refined search parameters, i.e. which elements are included and which are excluded. This refined search box may include a user interface element next to each search term to enable the user to deselect the search term. This may be a virtual button with an X, for example, as shown in the figure. The selection summary is updated each time a further selection is made to include or exclude a faceted search result as a search term”) (Col. 10 Ln. 20-35).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, the processor displays information indicating completion of setting of the tag as the search index, as taught by Dimassimo for the purpose so that a user could visually recognize which recognized query terms, entities, or filters had been applied, thereby improving usability, transparency of query processing, and search-result accuracy.
Jain specifically doesn’t disclose, so as to allow the user to visually recognize the information, however Cannon discloses, so as to allow a user to visually recognize the information (Examiner interprets that Dimassimo discloses the selection summary box showing the status of refined search parameters. Cannon further teaches a filter token object indicating that a filter or other processing is being applied. Thus, Dimassimo and Cannon collectively teach visual information by which the user can recognize that the tag/filter/search parameter has been set) (“the filter token object 1033 may be generated by the user interface system 502 and/or the semantic processing system 504 similar to the manner in which the model display objects are generated. In some cases, the filter token object 1033 is generated to indicate that a filter is being applied to the data from the statement 1010D that differs from filters applied to other statements 1010 (e.g., a different or custom time range is being used) and/or to indicate that a filter (or other processing) is being applied to the data in addition to whatever processing is to be done as a result of the corresponding statement 1010D. For example, the filter token object 1033 can indicate that an enriched data processing package will include additional query commands associated with the statement 1010D (or additional (search-related) statements) than what is shown in the data processing package 1009”) (Col. 73 Ln. 1-16, Col. 74 Ln. 17-35).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, so as to allow the user to visually recognize the information, as taught by Cannon for the purpose to use such a filter-token object in a query-processing interface to improve user understanding of active filters or refinements, improve transparency of the search process, and permit the user to select, modify, or remove active refinements.
Claims 3, 8, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Pub. 20150169582 (“Jain”) in view U.S. Pat. 9298816 (“Dimassimo”) in view U.S. Pat. 12169499 (“Cannon”) in view U.S. Pat. 6564213 (“Ortega”).
As per claims 3, Jain discloses, wherein the processor deletes the tag from the search string while the user is entering the search string during acquisition of the search string (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that the query processors adds, removes, or modifies terms from the query and removes terms through tokenization/truncation/stop-word filtering) (“query processor adds, removes or modifies terms from the query. The query processor provides a broad range of functionalities. For instance, it can add or recognize that two words that appear to be separate words actually identify a specific software entity or it can determine that a number appearing in a query is not just a numeric value but that it refers to a specific version or a number relevant to the specific configuration problem”) (0006, 0026-0030, 0035-0037).
Jain discloses, removing or modifying terms/tokens from a query and generating a modified query based on remaining query terms, but specifically doesn’t disclose, while the user is entering the search string during acquisition of the search string, however Ortega discloses, while the user is entering the search string during acquisition of the search string (Examiner interprets the Ortega suggesting autocompletion strings during query entry and autocompletion client that suggests strings as users enter queries) (“provide an autocompletion tool that suggests completed text strings to the user as the user enters text. For example, Microsoft's Internet Explorer browser automatically suggests completed URLs as the user enters text in the URL field; and the TextPlus.TM. for Palm tool suggests autocompletion words and phases (based on frequency of use) as users enter text within Palm Pilot.TM. applications. These tools generally operate based on text strings that have previously been entered on the particular PC, Palm Pilot, or other computing device. As a result, the tools generally are not helpful when the user enters a new term or phrase” and “FIGS. 2(a) and 2(b) illustrate the general form of a user interface that may be used by the autocompletion client 50 for both PCs and handheld computing devices. In this example, as the user enters a search query into a search field 60 of the Amazon.com web site (by voice, stylus, etc.), the autocompletion client displays suggested autocompletion terms and phrases in a drop-down box 62. As illustrated in FIG. 2(a), terms are displayed in an upper pane of the box and phrases are displayed in a lower pane of the box. In other implementations, the autocompletion client may only suggest one type of string (terms or phrases) without the other. As illustrated in FIG. 2(b), once the user has completed a term, the autocompletion client may only display suggested phrases …”) (Col. 1 Ln. 43- Col. 2 Ln. 28 and Col. 5 Ln. 23-36, See claims 38, 54, 56).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, while the user is entering the search string during acquisition of the search string, as taught by Ortega for the purpose to incorporate query-entry autocomplete functionality into Jain so that recognized query terms/tags could be identified and processed while the user is entering the search string, thereby reducing user input burden, improving query-entry efficiency, and increasing accuracy of the resulting search query.
As per claims 8, Jain discloses, wherein the processor displays a complemented character string, while the user is entering the search string, the complemented character string serving as a complement for the search string being input by the user, and deletes the tag from the search string at a timing of selection of the complemented character string (Examiner notes that the underlined limitation is disclosed by another prior art. Examiner interprets that the query processor adds, removes, or modifies terms from the query and generates a modified version of the query by passing the query through filters. Jain further discloses tokenizing the query, applying truncation and stop-word filtering to remove terms from query 101, and using the remaining/modified query terms to query a knowledge base index. Jain also discloses named-entity recognition, where recognized terms such as “SQL Server” may be tagged as “Software Entity” in an ontology model. The Examiner interprets the removed or modified query token as corresponding to the claimed deleted tag, and interprets Jain’s conversion of query 101 into a modified query compatible with an enhanced index or other index in knowledge base 140 as corresponding to setting the recognized tag/query information as a search index) (“query processor adds, removes or modifies terms from the query. The query processor provides a broad range of functionalities. For instance, it can add or recognize that two words that appear to be separate words actually identify a specific software entity or it can determine that a number appearing in a query is not just a numeric value but that it refers to a specific version or a number relevant to the specific configuration problem”) (0006, 0026-0030, 0035-0037).
Jain discloses, removing or modifying terms/tokens from a query and generating a modified query based on remaining query terms, but specifically doesn’t disclose, wherein the processor displays a complemented character string, while the user is entering the search string, the complemented character string serving as a complement for the search string being input by the user, however Ortega discloses, wherein the processor displays a complemented character string, while the user is entering the search string, the complemented character string serving as a complement for the search string being input by the user (Examiner interprets the Ortega suggesting autocompletion strings during query entry and autocompletion client that suggests strings as users enter query and allows selection of suggested string by click/tap. Examiner interprets the autocomplete string to the claimed complemented character string and maps selection timing to the claimed timing) (“provide an autocompletion tool that suggests completed text strings to the user as the user enters text. For example, Microsoft's Internet Explorer browser automatically suggests completed URLs as the user enters text in the URL field; and the TextPlus.TM. for Palm tool suggests autocompletion words and phases (based on frequency of use) as users enter text within Palm Pilot.TM. applications. These tools generally operate based on text strings that have previously been entered on the particular PC, Palm Pilot, or other computing device. As a result, the tools generally are not helpful when the user enters a new term or phrase” and “FIGS. 2(a) and 2(b) illustrate the general form of a user interface that may be used by the autocompletion client 50 for both PCs and handheld computing devices. In this example, as the user enters a search query into a search field 60 of the Amazon.com web site (by voice, stylus, etc.), the autocompletion client displays suggested autocompletion terms and phrases in a drop-down box 62. As illustrated in FIG. 2(a), terms are displayed in an upper pane of the box and phrases are displayed in a lower pane of the box. In other implementations, the autocompletion client may only suggest one type of string (terms or phrases) without the other. As illustrated in FIG. 2(b), once the user has completed a term, the autocompletion client may only display suggested phrases …”) (Col. 1 Ln. 43- Col. 2 Ln. 28 and Col. 5 Ln. 23-36, See claims 38, 54, 56).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, wherein the processor displays a complemented character string, while the user is entering the search string, the complemented character string serving as a complement for the search string being input by the user, as taught by Ortega for the purpose so that a displayed autocomplete string could serve as a complemented character string for the user’s partially entered search string, and so that selection of the complemented character string could trigger Jain’s known query-token processing/removal, thereby improving speed of query entry, reducing typing effort, and improving search-query accuracy.
As per claims 11, Jain discloses, removing/modifying query terms and generating a modified query, but specifically doesn’t disclose, the timing of deleting the tag upon selection of a complemented character string displayed while the user is entering the query, however Ortega discloses, wherein the processor deletes the tag from the search string at a timing of selection of a complemented character string displayed while the user is entering the search string, the complemented character string serving as a complement for the search string being input by the user (Examiner interprets the Ortega suggesting autocompletion strings during query entry and autocompletion client that suggests strings as users enter query and allows selection of suggested string by click/tap. Examiner interprets the autocomplete string to the claimed complemented character string and maps selection timing to the claimed timing) (“provide an autocompletion tool that suggests completed text strings to the user as the user enters text. For example, Microsoft's Internet Explorer browser automatically suggests completed URLs as the user enters text in the URL field; and the TextPlus.TM. for Palm tool suggests autocompletion words and phases (based on frequency of use) as users enter text within Palm Pilot.TM. applications. These tools generally operate based on text strings that have previously been entered on the particular PC, Palm Pilot, or other computing device. As a result, the tools generally are not helpful when the user enters a new term or phrase” and “The user interface may implement one or more methods for the user to perform the dual action of selecting and submitting a displayed autocompletion string with a single selection action, such as a single (or double) mouse click, a single (or double) tap on the string with a stylus, or a voice command. In one embodiment, for example, if the user taps or clicks once on a suggested string (term or phrase), the string is automatically added to the search field 60; and if the user taps or clicks twice on a string, the string is automatically submitted as the search query. In another embodiment, tapping or clicking once on a string causes the string to be submitted as the search query. In either case, the user can advantageously initiate the search without moving the stylus or mouse cursor away from the selected string. In embodiments that support voice recognition, each suggested string may be displayed in conjunction with a number (1, 2, 3, . . .) that can be used as a voice command to perform the dual action of selecting the string and initiating the search.…”) (Col. 1 Ln. 43- Col. 2 Ln. 28 and Col. 5 Ln. 36-54, See claims 38, 54, 56).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention for acquires a search string, the search string being entered by a user into an entry field, determines whether the acquired search string contains a tag based on tag information from a server, deletes the tag from the search string, and sets the tag as a search index, when determining that the search string contains the tag, generates, based on the set search index and a remaining character string, search information for searching targeted information, the remaining character string being made by deleting the tag from the search string, and acquires a search result based on the generated search information, as taught by Jain, wherein the processor deletes the tag from the search string at a timing of selection of a complemented character string displayed while the user is entering the search string, the complemented character string serving as a complement for the search string being input by the user, as taught by Ortega for the purpose to provide a predictable user-interface workflow in which the system recognizes and processes a completed query term at the moment the user selects it, thereby improving query-entry efficiency, reducing input errors, and increasing transparency of the search refinement process.
Response to Arguments
With regards to § 101 rejections:
The arguments filed on March 26th, 2026, with respect to the rejection(s) of claims 1-10 under 35 U.S.C 101 have been fully considered but are unpersuasive.
Applicant states that automatic parsing and restructuring of a search query entered into an entry field in a manner that simultaneously removes a tag from the textual search string while converting that tag into a structured search index, and then providing visual feedback to the user about this automated process. The determination of whether the search string contains a tag relies on tag information obtained from a server, which involves networked communication that cannot be performed in the human mind … and that the claimed improvement is analogous to Core Wireless Licensing S.A.R.L. v. LG Electronics, Inc., 880 F.3d 1356 (Fed. Cir. 2018). Remarks 5-7.
Applicant’s arguments have been fully considered but are not persuasive. The claim recites the alleged parsing, deletion, conversion, and display steps functionally and at a high level of generality, without reciting any specific technological implementation for how the tag is identified, how the tag is deleted from the search string, how the tag is converted into a search index, or how the display technically improves the operation of the computer or search system. At its core, the claim is directed to recognizing information in text, categorizing that information, separating it from remaining text, using the categorized information as a search criterion, and displaying the result of that categorization. These are information-processing steps that can be performed conceptually by a human using observation, judgment, and ordinary classification rules. Applicant’s reliance on “tag information from a server” does not change the analysis. Merely obtaining information from a server or performing the abstract idea in a networked computer environment does not integrate the exception into a practical application. The claim does not recite any improvement to server communication, network operation, data transmission, database structure, index architecture, or computer performance. Rather, the server is used as a generic source of information for carrying out the claimed categorization and search process. Similarly, the recited visual feedback does not provide a technological improvement. The claim broadly requires displaying information indicating that the tag has been set as a search index so that the user can visually recognize it. Displaying the result of an information-processing step is merely presenting the outcome of the abstract idea and does not, by itself, transform the claim into patent-eligible subject matter. Accordingly, the claimed processor merely automates the abstract mental/informational process using generic computer components, and the claim remains directed to organizing, categorizing, and searching information based on rules. Although the specification may describe a search device, server, tag information, and search processing environment, see Spec. ¶ 0043, those disclosures are generic computer-environment disclosures and do not show that the claimed invention improves the functioning of the server, search device, network, display, or search index.
The mere recitation that tag information is obtained “from a server” does not transform the claim into a specific technical implementation. The claim does not recite any particular server architecture, communication protocol, network-message structure, cache arrangement, synchronization technique, distributed-processing improvement, latency reduction, bandwidth reduction, memory improvement, or improvement to operation of the server or client device. Rather, the server is recited only as a generic source of information used to perform the abstract information-processing steps of identifying, categorizing, deleting, and using a tag as a search criterion. The Federal Circuit and USPTO guidance distinguish between claims that improve computer functionality itself and claims that merely use generic computer components to collect, process, transmit, or display information. See MPEP § 2106.05(a), (f), (g). Further, applicant’s reliance on Core Wireless is also unpersuasive. In Core Wireless, the claims were found eligible because they were directed to a particular manner of summarizing and presenting information in an electronic device user interface, including specific limitations on how an application summary was accessed and displayed in a way that improved the functioning of devices with small screens. Here, by contrast, the claims do not recite a particular improved user-interface structure, a specific screen arrangement, a limited summary window, a particular navigation path, or a specific display mechanism that improves operation of the computer or user interface. The claim merely requires displaying information indicating completion of setting the tag as a search index so that the user can visually recognize the information. Such generic presentation of the result of information processing is not analogous to the specific user-interface improvement in Core Wireless. To the extent Applicant relies on the Specification’s discussion of client-server interaction or networked implementation, such disclosure does not cure the claim deficiency. The claims, not merely the Specification, must recite the asserted technological improvement. While the Specification may describe that tag information can be obtained from a server or that client and server components may communicate, the claims do not require any specific technical mechanism by which the server communication improves network operation, search-index architecture, data storage, processing speed, or graphical-user-interface functionality. Unclaimed advantages described in the Specification cannot confer eligibility where the claim language itself remains directed to receiving information, classifying information, manipulating a search string, performing a search, and displaying the result. Thus, even considering Applicant’s argument that tag information is obtained from a server and that visual feedback is provided to the user, the claim still merely applies the abstract idea using generic client-server computing components. The claim does not integrate the judicial exception into a practical application under Step 2A Prong Two, and does not recite an inventive concept under Step 2B. Accordingly, the § 101 rejection is maintained. See MPEP §§ 2106.05(a)–(c), (e)– (h).
With regards to § 103 rejections:
Applicant's arguments, see pages 1-2, filed Jan 11th, 2026, with respect to the rejection(s) of claims 1-11 under 35 U.S.C 102/103 have been fully considered but are unpersuasive/moots on new ground of rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US. Pat. 9607100 (“Ware”).
Ware discloses, a method for providing inline search suggestions for a search string submitted by a user of an electronic marketplace is provided. A user submits a search string via a search interface in a computing device of the user. An electronic marketplace system receives the search string and identifies individual search terms in the search string that can be logically grouped together to form one or more segments in the search string. The electronic marketplace identifies a plurality of search strings submitted by a plurality of users that may relate to identified segments of search string submitted by the user. In one embodiment, the user selects a particular segment of the search string via the search interface. The electronic marketplace provides suggested search terms related to the identified segment to the user via the search interface.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GAUTAM UBALE whose telephone number is (571)272-9861. The examiner can normally be reached Mon-Fri. 7:00 AM- 6:30 PM PST.
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/GAUTAM UBALE/
Primary Examiner, Art Unit 3689
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