DETAILED ACTION
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 .
Response to Amendment
In response to the office action from 11/5/2025 the applicant has submitted an amendment filed 12/30/2025, amending claims 1, 5-7, 13, 15, cancelling claim 4, while arguing to traverse the prior art and other rejections. Applicant’s arguments have been fully considered and are moot with respect to new grounds of rejections further in view of prior art of record Pan et al. in view of Kushkuley et al. and Rivette et al. (US 2007/0208669) and for the reasons explained in the response to arguments.
Response to Arguments
Following a broad overview of the last office action on page 11 paragraph one, a section regarding 101 rejections is started by general remarks regarding the background of the invention (Page 11 paragraphs 2-3) followed by a copy of the first claim (page 11 last paragraph to the end of the sixth paragraph on page 12). This is followed by again some general remarks about the independent claims on page 13 where in the last part of that page it is concluded: “With the above-noted specific features detailing HOW the conditions for the hyponym search is generated, inappropriate associations between hypernyms and hyponyms that exist in the prior techniques can be avoided when the hypernym has a requirement in at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name”.
Related to this teaching, the amendment to the independent claim 1 recites: “storing search application condition information” “including an entry for each type of named-entities….” Followed by most items quoted above. Respectfully this causes tremendous addition of stored data and as a result fails to result at least in “smaller memory requirements …” as required by Enfish: i.e., see Enfish memorandum: “To make the determination of whether these claims are directed to an improvement in existing computer technology, the court looked to the teachings of the specification. Specifically, the court identified the specification’s teachings that the claimed invention achieves other benefits over conventional databases, such as increased flexibility, faster search times, and smaller memory requirements” (Enfish memorandum of 5/19/2016).
Therefore the examiner cannot respectfully agree with the request to “withdraw[] all these rejections” (page 13 last line).
Page 14 the first paragraph discusses the previous 112(b) rejections.
Due to the latest amendments the said rejections are overcome.
The remainder of the arguments discuss the prior art rejections but argue why the prior art of record fails to teach them.
Please visit the new office action for further details.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 13 and 15 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
The last part of limitation four recites: “both the first condition and the second condition being linked to the search target using the edge from the respective entry for generating the first condition and the second condition”.
In almost all the relevant teachings in the disclosure, only one “condition” (and not two DIFFERENT conditions) are taught to be associated with two “nodes” and one “edge”. Please see Sp. ¶ 0099: “In addition, the search application condition information 500-4 indicates, as a search application condition when the named-entity type is “usage”, a condition that a node to which another node indicating a word having a similarity of 0.5 or higher to the value in a usage tag is coupled via an edge indicating “usage” is searched for. Note that any existing approach may be used to calculate the similarity between character strings”. This associates a single “condition” with two “nodes” and one “edge”. Even teachings of Sp. ¶ 0135 and 139 teach one “search application condition information” helps generating another “search application condition” which then gets correlated with two “nodes” and one “edge”.
Regarding claims 2-3, 5-12 (dependent on claim 1), claim 14 (dependent on claim 13), and claim 16 (dependent on claim 15) as they do not obviate the problem noted in their parent claim they are thus rejected under similar rationale.
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, 13 and 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites about how one finds a “hyponym” (i.e. a “compound name” (Sp. ¶ 0156)) for every “hypernym” (“generic name” (Sp. ¶ 0156)) found in a “document” (e.g. a “search query” and/or “document data” (e.g. a “patent” of “thesis” and/or “the like” (Sp. ¶ 0056)). This is accomplished by “searching” a “knowledge graph” (something that holds “name-entities from [the] patent, thesis” “or the like” “specifying a relationship in each “named-entity”” “and graphing the relationships” (Sp. ¶ 0051)). Finally, an “associate[ion]” is made between the “extracted hypernym with the hyponym found in the search”.
In construction of the “knowledge graph”, what appears as “search application condition information” which is already stored in “a storage unit” and which defines how an “entity” (e.g., “named-entities” of plurality of types) may “include” “the hypernym” as well as the other “named-entities” placed as a “node” in the hypothetical “graph” may be connected to another “node” via an “edge” subject to a “search application criterion” which also defines “a relationship to a search target”.
These limitations under their broadest reasonable interpretation, cover performance of the limitations in the mind but for the recitation of a generic “computer”. That is, other than reciting “causing a computer” in the preamble, nothing in the claim limitations precludes the limitations precludes the limitations from practically being performed in the mind. For instance, suppose a person is reading a book (a document) and encounters the word “bank card” (a hypernym) and he needs more specific information about it. He could use a dictionary of some sort and/or Wikipedia (a knowledge graph) to search and determine that it is a broad definition of an ATM card and/or debit and/or credit card (associated hyponyms), and draw an association between them. These of course can all be done mentally and there is no need for a “computer” (stated in the preamble of the claim) given these steps and furthermore using these steps in a “computer”, do not help it running more efficiently.
The “knowledge graph” which depends on a massive storage of data is a function of e.g. compounds (an entity example) and their relationships in the form of a graph. This can be determined based on a relationship between e.g. two words (representing two nodes) and a relationship between them which requires nothing more than knowledge of vocabulary and/or certain scientific field (e.g., medicine and/or biology with respect to radicals and/or compounds). And in that case a human brain with that specific knowledge maps to the claim’s storage unit and he could merely write on a sheet of paper any two compounds (i.e., two nodes) with a relationship and specify their relationship (claim’s edge), to ultimately be used for a search target.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites one additional element, i.e. a “computer” tasked with the “storing”, “extracting”, “specifying”, “generating”, “searching”, and “associating” steps. The computer in all these steps is recited at a high-level of generality (i.e., as a generic computer performing generic computer functions corresponding to the “storing”, “extracting”, “specifying” “generating”, “searching” and “associating” steps. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is thus directed to an abstract idea.
The claim also does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using the “computer” to perform the “storing”, “extracting”, “specifying”, “generating” “searching”, and “associating” steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 2, the person in determining the “ATM”, “debit” and/or “credit” “card” could be found by looking up the dictionary and associated with the “bank card”.
Regarding claim 3, the person in determining the “ATM”, “debit” and/or “credit” “card” for the “bank card” could use a separate dictionary (e.g., one specialized in finance vocabulary) as an additional document determine associated hyponyms.
Regarding claims 5-7, in searching the Wikipedia a human could use conjunction operators “AND”, “OR” and “NOT” in conducting search and can write his search strategy using a pen and a paper.
Regarding claim 8, since the knowledge graph is a function of named entities (e.g. compounds) and relationships between them as a directed graph, it is completely predictable that changing the named entities will result in changing conditions generated for the named-entities including their hyponyms.
Regarding claims 9, and 10 “displaying” for determining “association between the hypernym” “and the” “hyponym” falls under the category of an observation activity which is classified as a mental activity.
Regarding claim 11, “outputting” a “hyponym” by either “display” and/or “audible” means will not require any particular device and can be achieved by either a pen and/or paper or by simple utterance.
Regarding claims 12, 14 and 16 to represent a “hypernym” and its determined “hyponym” as “lookup keywords” can be done by simply writing them on a sheet of paper.
Claim Rejections - 35 USC § 103
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, 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.
Claim(s) 1-3, 8, 12-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pan et al. (US 2022/0004711), and further in view of Kushkuley et al. (US 2019/0138659).
Regarding claim 1, Pan et al. do teach a non-transitory computer-readable recording medium storing an information processing program for causing a computer to execute processing (¶ 0050: “The present invention may be a system, a method and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention”)
comprising:
storing search application condition information in a storage unit, the search application condition information including an entry for each type of named-entities that include a hypernym, the type including at least one of a generic name of a compound for the hypernym, a compound name, a substituent name, a substructure name, a physical property name, a physical property value, and a usage name, and the entry including the named-entity type, an edge identifying a relationship to a search target, a node containing a value for the named-entity type and a search application criterion (¶ 0027 sentence 2: “A term taxonomy graph” (e.g. the knowledge graph) “can be a network graph which contains words as nodes” (uses nodes for “words” (e.g., a compound name)) “and vectors” (edges between the nodes) “connecting the nodes”; ¶ 0021 lines 5-6: “taxonomy graph” (i.e., the knowledge graph which provides “vector” connections (relations or condition information between “nodes” (e.g., “words” comprising named entities or generic names)) “stored on a server” (are stored in a storage unit), ¶ 0003 S2: “Domain specific term taxonomy graphs allow for optimized search engine results” (search target) “and assisting users in developing search queries by providing more general or specific terms” (depends on specific search application criteria) “related to the desired search subject. Further, virtual assistants require term taxonomy graphs to improve responses to commands from users”),
extracting at least one of the named-entities that include the hypernym from a document, the document being any one of a search query or document data that is regarded as an analysis object (¶ 0014 sentences 1-2: “a hypernym-hyponym induction engine (HHI) can receive a domain-specific corpus” (a document of data or analysis object) “analyze the domain specific corpus and extract” (undergoes extraction of) “identify hypernym” (a hypernym) “-hyponym from the extracted terms”);
the hypernym including a requirement in at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name (¶ 0004 lines 8+: “a processor can analyze the terms within the term” (associated hypernyms) “taxonomy graph” “and analyze the OOV” (appear in substituent names) “term to determine there is a similarity between a term within the term taxonomy graph and the OOV term above a threshold”; ¶ 0001: “The present invention relates generally to modeling hypernyms” (hypernyms) “and more specifically, to hypernym-hyponym pair induction into a taxonomy graph” (associated with “taxonomy graphs”) “of terms using data augmentation techniques”, “OOV”= “out of vocabulary”);
specifying a modifier character string that modifies the extracted hypernym from the document (¶ 0031 sentence 3+: “token may be a string of characters” (using a character string) “from a domain specific corpus” for “tokenization” of “words” (i.e. modifying a word e.g. a hypernym));
the modifier character string including a value for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym (the “word” (e.g., the “string of characters”) do comprise of “OOV”, wherein according to the abstract last 6 lines: “generated feature vectors” (generating a value) “of the OOV terms” (of the substituent name));
generating conditions to be applied when a knowledge graph is searched for a hyponym relevant for the extracted hypernym (¶ 0014 sentences 1-2: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” “analyze the domain specific corpus and extract” “identify hypernym-hyponym pairs” (generating conditions) “from extracted terms” (comprising e.g. name entities and/or “tokens” (modifier character strings) whose type and content are determined from the “domain” associated with the “domain-specific corpus”) “and can build a term taxonomy graph from its knowledge” (in a knowledge graph for searching a hyponym for extracted hypernyms); ¶ 0031 sentence 4: “tokenization” (modifier character string generation) “can include identifying term” (includes e.g. name entities and “tokens” (character string) in the “corpus” (the document)) “boundaries”);
the knowledge graph including information obtained by forming a directed graph with knowledge regarding compounds as nodes and relationships between the nodes as edges (¶ 0027 sentence 2: “A term taxonomy graph” (e.g. the knowledge graph) “can be a network graph which contains words as nodes” (uses nodes for “words” (e.g., a compound name)) “and vectors” (edges between the nodes) “connecting the nodes”),
searching the knowledge graph for the hyponym in accordance with the generated conditions (¶ 0014 sentence 1: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” “analyze” (search) “the domain specific corpus and extract” “identify hypernym-hyponym pairs” (by using the conditions) “from extracted terms and can build a term taxonomy graph from its knowledge base” (in the knowledge graph for a hyponym from the extracted hypernyms in the “hypernym-hyponym pairs”);
and associating the extracted hypernym with the hyponym found in the search (¶ 0037 last sentence: “For example, the similarities between hyponym and hypernyms” “the number of previous hyponyms for the hypernym, the averaged similarity of the previously associated hyponyms” (associating the extracted hypernym for the hyponym found in the search)).
Pan et al. do not specifically disclose:
The generating of the conditions referring to the search application condition information to generate a first condition identifying the hypernym and the search application criterion from the entry corresponding to the hypernym and a second condition identifying the value and the search application criterion from the entry corresponding to the type for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym from the modifier character string, both the first condition and the second condition being linked to the search target using the edge from the respective entry for generating the first condition and the second condition.
Kushkuley et al. do teach:
The generating of the conditions referring to the search application condition information to generate a first condition identifying the hypernym and the search application criterion from the entry corresponding to the hypernym and a second condition identifying the value and the search application criterion from the entry corresponding to the type for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym from the modifier character string, both the first condition and the second condition being linked to the search target using the edge from the respective entry for generating the first condition and the second condition (¶ 0021 lines 4+: “searching” (a search application information’s) “the data set” “to identify items of data meeting specified criteria” (for identifying a first search condition based on a criterion) “e.g., items containing” “hypernyms” (for an entry corresponding to a hypernym); ¶ 0028 S2: “a matrix that has search terms as its indices” (a second search condition) “and has values of “0” and “1”” (based on identifying a value) “reflecting site-specific relatedness” (and a criterion based on the type of terms being searched, e.g., ¶ 0022 lines 16+: “a casual clothing website” (a search) “”define” “khakis” (related to a substituent and/or usage name); in conducting each search both the “search” “based” on “specified criteria” related to “hypernym” (first condition) as well as that depending on “search terms” “indices” “reflecting” “relatedness” (second condition) associated with e.g. a substituent name are linked together to determine “search” “results” (search result (¶ 0023 S1))).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “hypernym” “hyponym” pair generation and management of Kushkuley et al. into those of Pan et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable to manage “search term[s] that [are] not among terms represented in a site-specific lookup table” as disclosed in Kushkuley et al. Abstract.
Regarding claim 2, Pan et al. do teach the non-transitory computer-readable recording medium according to claim 1, wherein the associating includes:
performing a lookup in the document for the hyponym found in the search (¶ 0014 sentences 1-2: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” “analyze” (performing a lookup) “the domain specific corpus” (in the document) “and extract terms” to “identify hypernym-hyponym” (for hyponym) “pairs”);
and associating the hypernym in the document with the hyponym found in the lookup in the document (¶ 0037 last sentence: “For example, the similarities between hyponym and hypernym” (associating the extracted hypernym from the document) “the number of previous hyponyms for the hypernym, the averaged similarity of the previously associated hyponyms” (with the hyponym found in the lookup)).
Regarding claim 3, Pan et al. do teach the non-transitory computer-readable recording medium according to claim 1, wherein the associating includes:
performing a lookup in another document different from the document for the hyponym found in the search (¶ 0017 sentence 1: “Additionally, in some embodiments the hypernym” (hypernym) “determined to be similar to the OOV” (obtained by looking up another different document) “in the term taxonomy graph” “which has a number of hyponyms” (for hyponym));
and associating the hypernym in the document with the hyponym found in the lookup in the another document (¶ 0036 lines 12+: “OOV induction engine 206, can compare the similarity” (associating) “of all hyponyms” (e.g. the hyponym in “OOV (the different document)) “with the hypernym” (with the hypernym)).
Regarding claim 8, Pan et al. do teach the non-transitory computer-readable recording medium according to claim 1, the processing further comprising:
searching the knowledge graph for the named-entities included in the modifier character string (¶ 0014 sentence 1: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” (comprises of “term[s]” (name entities and “tokens”) (character string)) “analyze” (search) “the domain specific corpus and extract” “identify hypernym-hyponym pairs” “from extracted terms and can build a term taxonomy graph from its knowledge base” (in the knowledge graph for a “hyponym” (named entities) from the extracted hypernyms in the “hypernym-hyponym pairs”);
and changing the conditions generated far the named-entities, based on the hyponym of the named-entities when the knowledge graph includes the hyponym of the named- entities found in the search (¶ 0017 sentence 2: a hypernym pair which has a number of hyponyms” (i.e., for every “hypernym” one obtains a plurality of “hyponyms” (named entities), therefore “hypernym-hyponym” pairs change which implies change of conditions based on the hyponym (named-entity) change),
wherein the searching includes searching the knowledge graph for the hyponym relevant to the hypernym in accordance with the changed conditions (¶ 0014 sentence 1: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” “analyze” (search) “the domain specific corpus and extract” “identify hypernym-hyponym pairs”(includes determining a new “hyponym” from) “from extracted terms and can build a term taxonomy graph from its knowledge base”(the knowledge graph) which is more relevant).
Regarding claim 12, Pan et al. do not specifically disclose the non-transitory computer-readable recording medium according to claim 1, wherein
the associating of the extracted hypernym with the hyponym found in the search includes setting the extracted hypernym and the hyponym found in the search as lookup keywords for when performing a lookup for a document according to the lookup query.
Kushkuley et al. do teach:
the non-transitory computer-readable recording medium according to claim 1, wherein
the associating of the extracted hypernym with the hyponym found in the search includes setting the extracted hypernym and the hyponym found in the search as lookup keywords for when performing a lookup for a document according to the lookup query (Abstract: “A method of filtering content from a data set includes accepting a search request directed to a data set associated with a site, the search request including a search term that is not among terms represented in a site-specific lookup table representing site -specific relatedness of terms in that data set, such related terms including any of synonyms, hypernyms and hyponyms” (hypernym and hyponyms associate with them) “generating an approximating lookup table” (stored in a lookup table for) “by applying a transformation function to a corpus lookup table, the corpus lookup table representing relatedness, in a general corpus, of terms in the data set; identifying terms represented in the approximating lookup table that are related terms” (as keywords or terms) “of the search term; and filtering from the data set digital content that includes any of the search term and the terms identified from the approximating table as related terms of the search term”).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “hypernym” “hyponym” pair generation and management of Kushkuley et al. into those of Pan et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable to mange “search term[s] that [are] not among terms represented in a site-specific lookup table” as disclosed in Kushkuley et al. Abstract.
Regarding claim 13, Pan et al. do teach an information processing method implemented by a computer (¶ 0050: “The present invention may be a system, a method and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention”)
The information processing method comprising:
storing search application condition information in a storage unit, the search application condition information including an entry for each type of named-entities that include a hypernym, the type including at least one of a generic name of a compound for the hypernym, a compound name, a substituent name, a substructure name, a physical property name, a physical property value, and a usage name, and the entry including the named-entity type, an edge identifying a relationship to a search target, a node containing a value for the named-entity type and a search application criterion (¶ 0027 sentence 2: “A term taxonomy graph” (e.g. the knowledge graph) “can be a network graph which contains words as nodes” (uses nodes for “words” (e.g., a compound name)) “and vectors” (edges between the nodes) “connecting the nodes”; ¶ 0021 lines 5-6: “taxonomy graph” (i.e., the knowledge graph which provides “vector” connections (relations or condition information between “nodes” (e.g., “words” comprising named entities or generic names)) “stored on a server” (are stored in a storage unit), ¶ 0003 S2: “Domain specific term taxonomy graphs allow for optimized search engine results” (search target) “and assisting users in developing search queries by providing more general or specific terms” (depends on specific search application criteria) “related to the desired search subject. Further, virtual assistants require term taxonomy graphs to improve responses to commands from users”),
extracting at least one of the named-entities that include the hypernym from a document, the document being any one of a search query or document data that is regarded as an analysis object (¶ 0014 sentences 1-2: “a hypernym-hyponym induction engine (HHI) can receive a domain-specific corpus” (a document of data or analysis object) “analyze the domain specific corpus and extract” (undergoes extraction of) “identify hypernym” (a hypernym) “-hyponym from the extracted terms”);
the hypernym including a requirement in at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name (¶ 0004 lines 8+: “a processor can analyze the terms within the term” (associated hypernyms) “taxonomy graph” “and analyze the OOV” (appear in substituent names) “term to determine there is a similarity between a term within the term taxonomy graph and the OOV term above a threshold”; ¶ 0001: “The present invention relates generally to modeling hypernyms” (hypernyms) “and more specifically, to hypernym-hyponym pair induction into a taxonomy graph” (associated with “taxonomy graphs”) “of terms using data augmentation techniques”, “OOV”= “out of vocabulary”);
specifying a modifier character string that modifies the extracted hypernym from the document (¶ 0031 sentence 3+: “token may be a string of characters” (using a character string) “from a domain specific corpus” for “tokenization” of “words” (i.e. modifying a word e.g. a hypernym));
the modifier character string including a value for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym (the “word” (e.g., the “string of characters”) do comprise of “OOV”, wherein according to the abstract last 6 lines: “generated feature vectors” (generating a value) “of the OOV terms” (of the substituent name));
generating conditions to be applied when a knowledge graph is searched for a hyponym relevant for the extracted hypernym (¶ 0014 sentences 1-2: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” “analyze the domain specific corpus and extract” “identify hypernym-hyponym pairs” (generating conditions) “from extracted terms” (comprising e.g. name entities and/or “tokens” (modifier character strings) whose type and content are determined from the “domain” associated with the “domain-specific corpus”) “and can build a term taxonomy graph from its knowledge” (in a knowledge graph for searching a hyponym for extracted hypernyms); ¶ 0031 sentence 4: “tokenization” (modifier character string generation) “can include identifying term” (includes e.g. name entities and “tokens” (character string) in the “corpus” (the document)) “boundaries”);
the knowledge graph including information obtained by forming a directed graph with knowledge regarding compounds as nodes and relationships between the nodes as edges (¶ 0027 sentence 2: “A term taxonomy graph” (e.g. the knowledge graph) “can be a network graph which contains words as nodes” (uses nodes for “words” (e.g., a compound name)) “and vectors” (edges between the nodes) “connecting the nodes”),
searching the knowledge graph for the hyponym in accordance with the generated conditions (¶ 0014 sentence 1: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” “analyze” (search) “the domain specific corpus and extract” “identify hypernym-hyponym pairs” (by using the conditions) “from extracted terms and can build a term taxonomy graph from its knowledge base” (in the knowledge graph for a hyponym from the extracted hypernyms in the “hypernym-hyponym pairs”);
and associating the extracted hypernym with the hyponym found in the search (¶ 0037 last sentence: “For example, the similarities between hyponym and hypernyms” “the number of previous hyponyms for the hypernym, the averaged similarity of the previously associated hyponyms” (associating the extracted hypernym for the hyponym found in the search)).
Pan et al. do not specifically disclose:
The generating of the conditions referring to the search application condition information to generate a first condition identifying the hypernym and the search application criterion from the entry corresponding to the hypernym and a second condition identifying the value and the search application criterion from the entry corresponding to the type for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym from the modifier character string, both the first condition and the second condition being linked to the search target using the edge from the respective entry for generating the first condition and the second condition.
Kushkuley et al. do teach:
The generating of the conditions referring to the search application condition information to generate a first condition identifying the hypernym and the search application criterion from the entry corresponding to the hypernym and a second condition identifying the value and the search application criterion from the entry corresponding to the type for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym from the modifier character string, both the first condition and the second condition being linked to the search target using the edge from the respective entry for generating the first condition and the second condition (¶ 0021 lines 4+: “searching” (a search application information’s) “the data set” “to identify items of data meeting specified criteria” (for identifying a first search condition based on a criterion) “e.g., items containing” “hypernyms” (for an entry corresponding to a hypernym); ¶ 0028 S2: “a matrix that has search terms as its indices” (a second search condition) “and has values of “0” and “1”” (based on identifying a value) “reflecting site-specific relatedness” (and a criterion based on the type of terms being searched, e.g., ¶ 0022 lines 16+: “a casual clothing website” (a search) “”define” “khakis” (related to a substituent and/or usage name); in conducting each search both the “search” “based” on “specified criteria” related to “hypernym” (first condition) as well as that depending on “search terms” “indices” “reflecting” “relatedness” (second condition) associated with e.g. a substituent name are linked together to determine “search” “results” (search result (¶ 0023 S1))).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “hypernym” “hyponym” pair generation and management of Kushkuley et al. into those of Pan et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable to mange “search term[s] that [are] not among terms represented in a site-specific lookup table” as disclosed in Kushkuley et al. Abstract.
Regarding claim 14, Pan et al. do not specifically disclose the information processing method according to claim 13, wherein
the associating of the extracted hypernym with the hyponym found in the search includes setting the extracted hypernym and the hyponym found in the search as lookup keywords for when performing a lookup for a document according to the lookup query.
Kushkuley et al. do teach:
the associating of the extracted hypernym with the hyponym found in the search includes setting the extracted hypernym and the hyponym found in the search as lookup keywords for when performing a lookup for a document according to the lookup query (Abstract: “A method of filtering content from a data set includes accepting a search request directed to a data set associated with a site, the search request including a search term that is not among terms represented in a site-specific lookup table representing site -specific relatedness of terms in that data set, such related terms including any of synonyms, hypernyms and hyponyms” (hypernym and hyponyms associate with them) “generating an approximating lookup table” (stored in a lookup table for) “by applying a transformation function to a corpus lookup table, the corpus lookup table representing relatedness, in a general corpus, of terms in the data set; identifying terms represented in the approximating lookup table that are related terms” (as keywords or terms) “of the search term; and filtering from the data set digital content that includes any of the search term and the terms identified from the approximating table as related terms of the search term”).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “hypernym” “hyponym” pair generation and management of Kushkuley et al. into those of Pan et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable to mange “search term[s] that [are] not among terms represented in a site-specific lookup table” as disclosed in Kushkuley et al. Abstract.
Regarding claim 15, Pan et al. do teach an information processing apparatus comprising:
Memory; and processor circuitry coupled to the memory, the processor circuitry being configured to perform processing (¶0041: “FIG. 4 depicts computer system 10, an example computer system representative of a dynamically switching user interface computer 10. Computer system 10 includes communications fabric 12, which provides communications between computer processor(s) 14, memory 16, persistent storage 18, network adaptor 28, and input/output (I/O) interface(s) 26. Communications fabric 12 can be implemented with any architecture designed for passing data and/or control information between processors (such as microprocessors, communications and network processors, etc.), system memory, peripheral devices, and any other hardware components within a system. For example, communications fabric 12 can be implemented with one or more buses”)
Including:
storing search application condition information in a storage unit, the search application condition information including an entry for each type of named-entities that include a hypernym, the type including at least one of a generic name of a compound for the hypernym, a compound name, a substituent name, a substructure name, a physical property name, a physical property value, and a usage name, and the entry including the named-entity type, an edge identifying a relationship to a search target, a node containing a value for the named-entity type and a search application criterion (¶ 0027 sentence 2: “A term taxonomy graph” (e.g. the knowledge graph) “can be a network graph which contains words as nodes” (uses nodes for “words” (e.g., a compound name)) “and vectors” (edges between the nodes) “connecting the nodes”; ¶ 0021 lines 5-6: “taxonomy graph” (i.e., the knowledge graph which provides “vector” connections (relations or condition information between “nodes” (e.g., “words” comprising named entities or generic names)) “stored on a server” (are stored in a storage unit), ¶ 0003 S2: “Domain specific term taxonomy graphs allow for optimized search engine results” (search target) “and assisting users in developing search queries by providing more general or specific terms” (depends on specific search application criteria) “related to the desired search subject. Further, virtual assistants require term taxonomy graphs to improve responses to commands from users”),
extracting at least one of the named-entities that include the hypernym from a document, the document being any one of a search query or document data that is regarded as an analysis object (¶ 0014 sentences 1-2: “a hypernym-hyponym induction engine (HHI) can receive a domain-specific corpus” (a document of data or analysis object) “analyze the domain specific corpus and extract” (undergoes extraction of) “identify hypernym” (a hypernym) “-hyponym from the extracted terms”);
the hypernym including a requirement in at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name (¶ 0004 lines 8+: “a processor can analyze the terms within the term” (associated hypernyms) “taxonomy graph” “and analyze the OOV” (appear in substituent names) “term to determine there is a similarity between a term within the term taxonomy graph and the OOV term above a threshold”; ¶ 0001: “The present invention relates generally to modeling hypernyms” (hypernyms) “and more specifically, to hypernym-hyponym pair induction into a taxonomy graph” (associated with “taxonomy graphs”) “of terms using data augmentation techniques”, “OOV”= “out of vocabulary”);
specifying a modifier character string that modifies the extracted hypernym from the document (¶ 0031 sentence 3+: “token may be a string of characters” (using a character string) “from a domain specific corpus” for “tokenization” of “words” (i.e. modifying a word e.g. a hypernym));
the modifier character string including a value for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym (the “word” (e.g., the “string of characters”) do comprise of “OOV”, wherein according to the abstract last 6 lines: “generated feature vectors” (generating a value) “of the OOV terms” (of the substituent name));
generating conditions to be applied when a knowledge graph is searched for a hyponym relevant for the extracted hypernym (¶ 0014 sentences 1-2: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” “analyze the domain specific corpus and extract” “identify hypernym-hyponym pairs” (generating conditions) “from extracted terms” (comprising e.g. name entities and/or “tokens” (modifier character strings) whose type and content are determined from the “domain” associated with the “domain-specific corpus”) “and can build a term taxonomy graph from its knowledge” (in a knowledge graph for searching a hyponym for extracted hypernyms); ¶ 0031 sentence 4: “tokenization” (modifier character string generation) “can include identifying term” (includes e.g. name entities and “tokens” (character string) in the “corpus” (the document)) “boundaries”);
the knowledge graph including information obtained by forming a directed graph with knowledge regarding compounds as nodes and relationships between the nodes as edges (¶ 0027 sentence 2: “A term taxonomy graph” (e.g. the knowledge graph) “can be a network graph which contains words as nodes” (uses nodes for “words” (e.g., a compound name)) “and vectors” (edges between the nodes) “connecting the nodes”),
searching the knowledge graph for the hyponym in accordance with the generated conditions (¶ 0014 sentence 1: “a hypernym-hyponym induction engine (HHIE) can receive a domain-specific corpus” “analyze” (search) “the domain specific corpus and extract” “identify hypernym-hyponym pairs” (by using the conditions) “from extracted terms and can build a term taxonomy graph from its knowledge base” (in the knowledge graph for a hyponym from the extracted hypernyms in the “hypernym-hyponym pairs”);
and associating the extracted hypernym with the hyponym found in the search (¶ 0037 last sentence: “For example, the similarities between hyponym and hypernyms” “the number of previous hyponyms for the hypernym, the averaged similarity of the previously associated hyponyms” (associating the extracted hypernym for the hyponym found in the search)).
Pan et al. do not specifically disclose:
The generating of the conditions referring to the search application condition information to generate a first condition identifying the hypernym and the search application criterion from the entry corresponding to the hypernym and a second condition identifying the value and the search application criterion from the entry corresponding to the type for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym from the modifier character string, both the first condition and the second condition being linked to the search target using the edge from the respective entry for generating the first condition and the second condition.
Kushkuley et al. do teach:
The generating of the conditions referring to the search application condition information to generate a first condition identifying the hypernym and the search application criterion from the entry corresponding to the hypernym and a second condition identifying the value and the search application criterion from the entry corresponding to the type for the at least one of the substituent name, the substructure name, the physical property name, the physical property value, and the usage name for the hypernym from the modifier character string, both the first condition and the second condition being linked to the search target using the edge from the respective entry for generating the first condition and the second condition (¶ 0021 lines 4+: “searching” (a search application information’s) “the data set” “to identify items of data meeting specified criteria” (for identifying a first search condition based on a criterion) “e.g., items containing” “hypernyms” (for an entry corresponding to a hypernym); ¶ 0028 S2: “a matrix that has search terms as its indices” (a second search condition) “and has values of “0” and “1”” (based on identifying a value) “reflecting site-specific relatedness” (and a criterion based on the type of terms being searched, e.g., ¶ 0022 lines 16+: “a casual clothing website” (a search) “”define” “khakis” (related to a substituent and/or usage name); in conducting each search both the “search” “based” on “specified criteria” related to “hypernym” (first condition) as well as that depending on “search terms” “indices” “reflecting” “relatedness” (second condition) associated with e.g. a substituent name are linked together to determine “search” “results” (search result (¶ 0023 S1))).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “hypernym” “hyponym” pair generation and management of Kushkuley et al. into those of Pan et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable to manage “search term[s] that [are] not among terms represented in a site-specific lookup table” as disclosed in Kushkuley et al. Abstract.
Regarding claim 16, Pan et al. do not specifically disclose the information processing apparatus according to claim 15, wherein
the associating of the extracted hypernym with the hyponym found in the search includes setting the extracted hypernym and the hyponym found in the search as lookup keywords for when performing a lookup for a document according to the lookup query.
Kushkuley et al. do teach:
the associating of the extracted hypernym with the hyponym found in the search includes setting the extracted hypernym and the hyponym found in the search as lookup keywords for when performing a lookup for a document according to the lookup query (Abstract: “A method of filtering content from a data set includes accepting a search request directed to a data set associated with a site, the search request including a search term that is not among terms represented in a site-specific lookup table representing site -specific relatedness of terms in that data set, such related terms including any of synonyms, hypernyms and hyponyms” (hypernym and hyponyms associate with them) “generating an approximating lookup table” (stored in a lookup table for) “by applying a transformation function to a corpus lookup table, the corpus lookup table representing relatedness, in a general corpus, of terms in the data set; identifying terms represented in the approximating lookup table that are related terms” (as keywords or terms) “of the search term; and filtering from the data set digital content that includes any of the search term and the terms identified from the approximating table as related terms of the search term”).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “hypernym” “hyponym” pair generation and management of Kushkuley et al. into those of Pan et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable to mange “search term[s] that [are] not among terms represented in a site-specific lookup table” as disclosed in Kushkuley et al. Abstract.
Claim(s) 5-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pan et al. in view of Kushkuley et al., and further in view of Rivette et al. (US 2007/0208669).
Regarding claim 5, Pan et al. in view of Kushkuley et al. do not specifically disclose the non-transitory computer-readable recording medium according to claim 1, wherein
a plurality of the named-entities is included in the modifier character string and the plurality of the named-entities involves an alternative conjunction, the generating of the conditions is performed for each of the plurality of the named- entities, and an OR condition is set between the conditions respectively generated for each of the plurality of the named-entities.
Rivette et al. do teach the non-transitory computer-readable recording medium according to claim 1, wherein a plurality of the named-entities is included in the modifier character string and the plurality of the named-entities involves an alternative conjunction, the generating of the conditions is performed for each of the plurality of the named- entities, and an OR condition is set between the conditions respectively generated for each of the plurality of the named-entities ( ¶ 1811: “the query asset package module 33504 displays an additional form that allows the user to enter a search expression” (a search application condition) “that specifies a logical conditional expression of ANDs, ORs” (involving an or conjunction) “and NOTs (with parenthetical grouping) combining assets ((Asset 1 AND Asset 2) OR Asset 3)” (between named entities) “which it gathers with the Query Assets use case”).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “search expression” construction based on “logical conditional expression” of Rivette et al. into “searching” that “meet[] specified criteria” of Kushkuley et al. in Pan et al. in view of Kushkuley et al. would enable Pan et al. in view of Kushkuley et al. to quantitatively emulate very complicated criteria involving two or more conditions such as “combining assets” (conditions based on) “((Asset 1 AND Asset 2) OR Asset 3)” (two or more logical relations between numerous named entities) as disclosed in Rivette et al. ¶ 1811.
Regarding claim 6, Pan et al. in view of Kushkuley et al. do not specifically disclose the non-transitory computer-readable recording medium according to claim 1, wherein
a plurality of the named-entities is included in the modifier character string and the plurality of the named-entities involves a linking conjunction, the generating of the conditions is performed for each of the plurality of the named- entities, and an AND conditions is set between the conditions respectively generated for each of the plurality of the named-entities.
Rivette et al. do teach the non-transitory computer-readable recording medium according to claim 1, wherein a plurality of the named-entities is included in the modifier character string and the plurality of the named-entities involves a linking conjunction, the generating of the conditions is performed for each of the plurality of the named- entities, and an AND condition is set between the conditions respectively generated for each of the plurality of the named-entities ( ¶ 1811: “the query asset package module 33504 displays an additional form that allows the user to enter a search expression” (a search application condition) “that specifies a logical conditional expression of ANDs” (involving a conjunction of AND type) “ORs” “and NOTs (with parenthetical grouping) combining assets ((Asset 1 AND Asset 2) OR Asset 3)” (between named entities) “which it gathers with the Query Assets use case”).
For obviousness to combine Pan et al. in view of Kushkuley et al. and Rivette et al. see claim 5.
Regarding claim 7, Pan et al. in view of Kushkuley et al. do not specifically disclose the non-transitory computer-readable recording medium according to claim 1, wherein
a plurality of the named-entities is included in the modifier character string and a negative word is involved with at least one of the named-entities, the generating of the conditions is performed for each of the plurality of the named- entities, and a NOT condition is set for the conditions generated for the at least one of the named-entities.
Rivette et al. do teach the non-transitory computer-readable recording medium according to claim 1, wherein
a plurality of the named-entities is included in the modifier character string and a negative word is involved with at least one of the named-entities, the generating of the conditions is performed for each of the plurality of the named- entities, and a NOT condition is set for the conditions generated for the at least one of the named-entities ( ¶ 1811: “the query asset package module 33504 displays an additional form that allows the user to enter a search expression” (a search application condition) “that specifies a logical conditional expression of ANDs” “ORs” “and NOTs” (involving a conjunction of NOT type) “with parenthetical grouping” “combining assets ((Asset 1 AND Asset 2) OR Asset 3)” (between named entities) “which it gathers with the Query Assets use case”).
For obviousness to combine Pan et al. in view of Kushkuley et al. and Rivette et al. see claim 5.
Claim Rejections - 35 USC § 103
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, 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.
Claim(s) 9-11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pan et al. in view Kushkuley et al., and further in view of Suzuki et al. (US 2020/0097596).
Regarding claim 9, Pan et al. in view of Kushkuley et al. do not specifically disclose the non-transitory computer-readable recording medium according to claim 2, the processing further comprising, when displaying the document, displaying the document such that association between the hypernym and the hyponym that have been associated in the document is specifiable.
Suzuki et al. do teach the non-transitory computer-readable recording medium according to claim 2, the processing further comprising, when displaying the document, displaying the document such that association between the hypernym and the hyponym that have been associated in the document is specifiable (¶ 0014: “FIG. 7 illustrates a schematic of a graphical user interface displaying” (displaying) “a result of hypernym-hyponym relation” (an association between a hypernym and hyponym from e.g. a document associated with the first row in Fig. 7 which is about one brand of hyponym associated with “electrolytes” ) “extraction according to an exemplary embodiment of the present invention”).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “display” methods of Suzuki et al. for “hypernym” “hyponym” “pairs” into the “display” device of Pan et al. in Pan et al. in view of Kushkuley et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable Pan et al. in view of Kushkuley et al. to enable “selecting reliable pairs from candidates of hypernym/hyponym list[]” as disclosed in Suzuki et al. ¶ 0079 last sentence.
Regarding claim 10, Pan et al. in view of Kushkuley et al. do not specifically disclose the non-transitory computer-readable recording medium according to claim 3, the processing further comprising, when displaying the document and the another document, displaying the document and the another document such that association between the hypernym in the document and the hyponym in the another document that have been associated is specifiable.
Suzuki et al. do teach the non-transitory computer-readable recording medium according to claim 3, the processing further comprising, when displaying the document and the another document, displaying the document and the another document such that association between the hypernym in the document and the hyponym in the another document that have been associated is specifiable (¶ 0014: “FIG. 7 illustrates a schematic of a graphical user interface displaying” (displaying) “a result of hypernym-hyponym relation” (an association between a hypernym and hyponym from e.g. a document associated with the first row in Fig. 7 which shows four rows corresponding to four different brands of “electrolytes” associated with four documents) “extraction according to an exemplary embodiment of the present invention” (e.g. the first two shows “electrolytes” (hypernym) with its associated hyponym of one brand (document) and the second rows shows association of “electrolytes” (hypernym) with another hyponym brand (a second different document)).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “display” methods of Suzuki et al. for “hypernym” “hyponym” “pairs” into the “display” device of Pan et al. in Pan et al. in view of Kushkuley et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable Pan et al. in view of Kushkuley et al. to enable display of a single “hypernym” with plurality of “hyponyms” with specific mention of their association in each case as depicted in Fig. 7 thereby providing a comprehensive list of the term.
Regarding claim 11, Pan et al. in view of Kushkuley et al. do not specifically disclose the non-transitory computer-readable recording medium according to claim 2, wherein
the associating includes outputting the hyponym found in the search in association with the hypernym in the document.
Suzuki et al. do teach the non-transitory computer-readable recording medium according to claim 2, wherein
the associating includes outputting the hyponym found in the search in association with the hypernym in the document (¶ 0014: “FIG. 7 illustrates a schematic of a graphical user interface displaying” (outputting) “a result of hypernym-hyponym” (a hyponym) “relation” (associated with a hypernym and hyponym from e.g. a document associated with the first row in Fig. 7) “extraction according to an exemplary embodiment of the present invention”).
It would have therefore been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the “display” methods of Suzuki et al. for “hypernym” “hyponym” “pairs” into the “display” device of Pan et al. in Pan et al. in view of Kushkuley et al. would enable the combined systems and their associated methods to perform in combination as they do separately and to further enable Pan et al. in view of Kushkuley et al. to enable “selecting reliable pairs from candidates of hypernym/hyponym list[]” as disclosed in Suzuki et al. ¶ 0079 last sentence.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 FARZAD KAZEMINEZHAD whose telephone number is (571)270-5860. The examiner can normally be reached 10:30 am to 11:30 pm.
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/Farzad Kazeminezhad/
Art Unit 2653
March 30th 2026.