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 .
Status of Claims
Claims 1-20 are pending of which claims 1, 8 and 15 are in independent form.
Claims 1-20 are rejected on the ground of nonstatutory double patenting.
Claims 1-20 are rejected under 35 U.S.C. 101.
Claims 1-20 are rejected under 35 U.S.C. 103.
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-21 of U.S. Patent No. US 12222950 B2. Although the claims at issue are not identical, they are not patentably distinct from each other.
Claims 1-20 are mapped directly one to one with claims 1-21 of the U.S. Patent No. US 12222950 B2.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The claim(s) recite(s) data sharing platforms, and particularly to searching and ranking data sets within a data sharing platform.
With respect to step 1 of the patent subject matter eligibility analysis, the claims are directed to a process, machine, manufacture, or composition of matter.
Independent claim 1 is directed to a system which includes a memory and a processing device, which is directed to one of the four statutory subject matters.
Independent claim 8 is directed to a method, which is a process.
Independent claim 15 directed to non-transitory computer readable medium, which is directed to one of the four statutory subject matters.
Independent All other claims depend on claims 1, 8 and 15. As such, claims 1-20 are directed to a statutory category.
Regarding claims 1, 8 and 15:
With respect to step 2A, prong one (Judicial Exception), the claims recite an abstract idea, law of nature, or natural phenomenon. Specifically, the following limitations recite mathematical concepts and/or mental processes and/or certain methods of organizing human activity.
The claim recites sequence of operations that amount to information organization, searching, evaluation, and ranking directed to an abstract idea:
Generating a data dictionary with metadata describing shared data and objects (tables, schema, views, functions);
Receiving a query with search term;
Retrieving data listings based on the search terms;
Generating listing specific signals and external activity signals;
Ranking the data listings based on metadata and signals; and
Presenting ranking results to a data consumer.
These steps fall into recognized abstract idea:
Collecting and analyzing information (mathematical concept/algorithm: metadata, activity signals)
Organizing and ranking information (mental process: data listings based on signals);
Presenting information (insignificant application: ranked listings to a consumer).
These operations are considered mental process (such as catalog searching, market place ranking, and recommendation system) performed on generic off the shelf technology.
There are no steps performed that provides a technical improvement to the computing system itself (improved data structure, improved model architecture, improved hardware).
Thus, the claims recite an abstract idea (mental process/information organization).
With respect to step 2A, Prong Two (Particular Application), the claims do not recite additional elements that integrate the judicial exception into a practical application. The following limitations are considered “additional elements” and explanation will be given as to why these “additional elements” do not integrate the judicial exception into a practical application.
The claims recite the use of:
The recited components (memory, processing device, could computing platform) are generic computer components,
These components merely use conventional computer components as tools to execute the abstract idea.
The limitations fail to transform the exception into a practical application. There is also no improvements to computer functionality or any specific technical solution to a computer centric problems (no improvements to data structure, or improved query execution mechanism, reduced latency, memory usage, or network overhead, or any technical modification to how the cloud platform itself operates). The computer merely used as a tool to: store metadata, execute search, calculate rankings, and display results, which are abstract improvements to information presentation and not technical improvements.
There is no recitation of, a new data structure that changes computer operation, improved communication, an unconventional indexing technique, a specific hardware solution.
Instead the claims recite conventional and generic computer functions performed in a routine manner, which does not amount to a practical application.
With respect to Step 2B. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The recited components are merely generic computer/database elements performing their routine, well-understood, and conventional functions. See Alive, MPEP 2016.05(d).
The steps mentioned in the independent claims merely constitutes standard distributed-database behavior, such and basic replication, mirroring, and ownership transfer. Courts have consistently helped such high level information management operations are conventional.
The claims recite only, without significantly more, listing specific signals and external signals are result oriented and functional (without technical implementation), no practical algorithm, signal generation technique, or ranking mechanism. All are routine, conventional operations business/ market place logic.
Considering claims as a whole, the ordered combination of elements also reflects nothing more than the typical workflow of distributed systems, and therefore DOES NOT add “significantly more” than the abstract idea.
Such generic, high‐level, and nominal involvement of a computer or computer‐based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent‐eligible, as noted at pg.74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo. Further, See, e.g., Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359‐60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093‐94 (Fed. Cir. 2015) ("Just as Diehr could not save the claims in Alice, which were directed to 'implement[ing] the abstract idea of intermediated settlement on a generic computer', it cannot save O/P's claims directed to implementing the abstract idea of price optimization on a generic computer.") (citations omitted). See also, Affinity Labs of Texas LLC v. DirecTV LLC, 838 F.3d 1253, 1257‐1258 (Fed. Cir. 2016) (mere recitation of a GUI does not make a claimpatent‐eligible); Intellectual Ventures I LLC v. Capital One Bank, 792 F.3d 1363, 1370 (Fed. Cir. 2015) ("the interactive interface limitation is a generic computer element".).
The additional elements are broadly applied to the abstract idea at a high level of generality ("similar to how the recitation of the computer in the claims in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer,") as explained in MPEP § 2106.05(f)) and they operate in a well‐understood, routine, and conventional manner.
MPEP § 2106.0S(d)(II) sets forth the following:
The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
• Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec ... ; TLI Communications LLC v. AV Auto. LLC ... ; OIP Techs., Inc., v. Amazon.com, Inc ... ; buySAFE, Inc. v. Google, Inc ... ;
• Performing repetitive calculations, Flook ... ; Bancorp Services v. Sun Life ... ;
• Electronic recordkeeping, Alice Corp ... ; Ultramercial ... ;
• Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc ... ;
• Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank ... ; and
• A web browser's back and forward button functionality, Internet Patent
• Corp. v. Active Network, Inc. ...
. . . Courts have held computer-implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself.
The dependent claims have been fully considered as well, however, similar to the findings for claims above, these claims are similarly directed to the “Mental Processes” grouping of abstract ideas set forth in the 2019 PEG, without integrating it into a practical application and with, at most, a general purpose computer that serves to tie the idea to a particular technological environment, which does not add significantly more to the claims. The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to significantly more than the abstract idea.
Looking at the claim as a whole does not change this conclusion and the claim is ineligible.
Regarding claims 2, 9 and 16,
The claim recites:
determine logical, semantic, and topic-related equivalences for search terms; generating and processing a second query to using those equivalences.
This is merely determining equivalences between terms in linguistic interpretation and semantic analysis (mental process). Generating a reformulated query simply broadens information retrieval scope, not a technical improvement. It does not improve execution, indexing structures, or computer functionality.
This does not change the nature of the abstract idea. It does not add a technical improvement to an abstract idea, such as improving computer functionality, data structure, or processing architecture.
There is no practical application, and no inventive step, the claims are still considered abstract.
Regarding claims 3, 10 and 17,
The claim recites:
listing-specific signals including TF-IDF, distance between search terms, data characteristic, or lexical diversity.
TF-IDF, term distance, and lexical diversity are mathematical/ statistical algorithms/concepts. Applying mathematical scoring to text data is abstract data analysis, not a technical improvement. There is no improvements to data storage, search efficiency, or computer architecture.
This does not change the nature of the abstract idea. It does not add a technical improvement to an abstract idea, such as improving computer functionality, data structure, or processing architecture.
There is no practical application, and no inventive step, the claims are still considered abstract.
Regarding claims 4, 11 and 18,
The claim recites:
external signals includes at least one of, a popularity score, a click-through rate, account-specific data, or user-specific data.
Popularity and click-through metrics are measurements of human activity. Ranking based on user behavior is organizing and evaluating information, and simply uses generic computing to apply market place logic, not a technical improvement.
This does not change the nature of the abstract idea. It does not add a technical improvement to an abstract idea, such as improving computer functionality, data structure, or processing architecture.
There is no practical application, and no inventive step, the claims are still considered abstract.
Regarding claims 5, 12 and 19,
The claim recites:
receiving a browser request to load a web page; provide logic with the web page data, to generate listing-specific signals and external signals.
Receiving browser requests and serving web page data are conventional web operations. Providing logic, is functional and result oriented without technical implementation. This does not improve networking, browser behavior, or web rendering technology.
This does not change the nature of the abstract idea. It does not add a technical improvement to an abstract idea, such as improving computer functionality, data structure, or processing architecture.
There is no practical application, and no inventive step, the claims are still considered abstract.
Regarding claims 6, 13 and 20,
The claim recites:
present a description of each listing.
Presenting descriptive information is simply information display (insignificant application). Information presentation alone does not constitute a technical improvement.
This does not change the nature of the abstract idea. It does not add a technical improvement to an abstract idea, such as improving computer functionality, data structure, or processing architecture.
There is no practical application, and no inventive step, the claims are still considered abstract.
Regarding claims 7, and 14,
The claim recites:
generate listing-specific signals and external signals by analyzing the data dictionary.
Analyzing metadata to derive signals is data evaluation and interpretation. This is simply repurposing existing information for scoring and ranking. This does not modify data structure, storage formats, or computing performance.
This does not change the nature of the abstract idea. It does not add a technical improvement to an abstract idea, such as improving computer functionality, data structure, or processing architecture.
There is no practical application, and no inventive step, the claims are still considered abstract.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Miller; Richard D. et al. (US 20200226143 A1) [Miller], and further in view of Munemann; Jean Alexandera (US 20170154040 A1) [Munemann] in view of Glickman; Matthew et al. (US 20210081439 A1) [Glickman].
Regarding claims 1, 8 and 15, Miller teaches, a system, comprising: a memory; and a processing device operatively coupled to the memory (See Figs. 1 and 2), the processing device to:
receiving a query comprising a set of search terms (Miller [0048]: The related terms
element 428 displays one or more terms related to one or more of the search terms in the search query.)
retrieving a set of data listings [in the data exchange of the cloud computing platform] based on the set of search terms of the query (Miller [0051]: Still referring to FIG. 4, the graphical user interface 400 includes a results listing element 440. The results listing element 440 may display a preview or otherwise display of a result set of documents identified by searching the document database with the search query, including a first document result 442a, a second document result 4425p, a third document result 442¢, and a fourth document result 4424. In one embodiment, the results listing element 440 provides preview or other display of a subset of the result set of documents. In another embodiment, all of the returned electronic documents are provided in results listing element 440.);
generating, for each data listing of the set of data listings, a set of listing-specific signals and a set of external signals, wherein each external signal of the set of external signals correspond to a measure of activity of the data listing of a set of listings in the data exchange [of the cloud computing platform] (Miller [0036]: Each of the query term nodes 422 is sized relative to the other nodes based on the relative prevalence of the terms among the most relevant portions (e.g., snippets) from each analyzed results document and any semantically related concepts contained in the topmost relevant documents that were returned during a search using the natural language query);
presenting, based on the ranking, the set of data listings to a data consumer (In the embodiment depicted in FIG. 4, the graphical user interface 400 is updated to display relevant portions of the top four ranked documents of the result set of documents in the results listing element 440, the query visualization and manipulation element 420 is updated to show the various term nodes 422, topic nodes 424, and connectors 423, the related terms element 428 is updated to show the top five related terms and five additional related terms, color coding terms in the query visualization and manipulation element 420 to match corresponding terms shown in the excerpts of the document results 442 ¶ [0085]).
Miller does not clearly teach, of the cloud computing platform; ranking the set of data listings based on: the set of listing -specific signals; the set of external signals for each data listing of the set of data listings.
Munemann discloses, of the cloud computing platform; in the data exchange of the cloud computing platform (¶ [0158], cloud storage).
ranking the set of data listings based on: the data dictionary (For example, if a user were browsing an electronic shopping site, as an example of generating a suggestion, an evaluation of keywords may be utilized to make suggestion and/or recommendations associated with new items, such as new items to be added to an electronic catalog. For example, a description for a new item may be evaluated in order to determine keywords associated with the new item. The keywords for the new item may then be compared to respective lists of keywords associated with various groups of items (e.g., subsets of a graph, etc.) included in the electronic catalog ¶ [0080]);
the set of listing -specific signals (Munemann [0111 — 0112] teaches, “In block 512, the documents may be ranked based on the lexicon for the user and the user-related preferences. The highest ranking webpages may be selected is selected, as this maybe the webpage documents that would be most suitable for the user's query. At operation 514, the highest ranking websites is presented to the user. It may be presented either on the user device. The total number of websites presented to the user may vary based on the size of the users’ browser screen and preferences.” Here, documents are similarly ranked based on the user preference signals);
the set of external signals for each data listing of the set of data listings (Munemann [0044]: In the example system, the website 106 may have an automated tagging or a system tag based on the words or other tokens utilized in the website. For example, if a website has text for the words “fast ferry,” one can associate that with search query relating to a “ship,” for example. However, these automated system tags may not be able to provide semantic understanding of a particular document. Further, users may browse a particular website and for that particular website 106 and may provide user-specific tagging.).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to incorporate the teaching of Miller et al. to the Munemann’s system by adding the feature of ranking search results. The references (Miller and Munemann) teach features that are analogous art and they are directed to the same field of endeavor, such as data search. Ordinary skilled artisan would have been motivated to do so to provide Miller’s system with enhanced search results. (See Munemann [ Abstract], [0034], [0036], [0060], [0111-0112]). One of the biggest advantages of network machine learning database algorithms is their ability to improve over time. Machine learning technology typically improves efficiency and accuracy thanks to the ever-increasing amounts of data that are processed.
However neither one of the Miller or Munemann explicitly facilitates generating a data dictionary for each of a set of data listings in a data exchange of a cloud computing platform, the data dictionary for each of the set of data listings comprising: first metadata describing data shared by a data listing; and second metadata describing individual objects included in the data shared by the data listing including tables, schemas, views, and functions.
Glickman discloses, generating a data dictionary for each of a set of data listings in a data exchange of a cloud computing platform, the data dictionary for each of the set of data listings (The exchange data 200 may further include a catalog 220. The catalog 220 may include a listing of all available listings 202 and may include an index of data from the metadata 204 to facilitate browsing and searching according to the methods described herein ¶ [0055]. Note that where there a multiple instances of the virtual warehouse 131 on different cloud computing platforms, the catalog 220 of one instance of the virtual warehouse 131 may store listings or references to listings from other instances on one or more other cloud computing platforms 110 ¶ [0056]. The exchange manager 124 may further create 412 a listing 202 including the data submitted at step 406 and may further create an entry in the catalog 220. For example, keywords, descriptive text, and other items of information in the metadata may be indexed to facilitate searching ¶ [0069]) comprising:
first metadata describing data shared by a data listing (A listing 202 may include metadata 204 describing the shared data. The metadata 204 may include some or all of the following information: an identifier of the sharer of the shared data, a URL associated with the sharer, a name of the share, a name of tables, a category to which the shared data belongs, an update frequency of the shared data, a catalog of the tables, a number of columns and a number of rows in each table, as well as name for the columns ¶ [0041]. Also see ¶ [0055], [0057], [0066]-[0068]); and
second metadata describing individual objects included in the data shared by the data listing including tables, schemas, views, and functions (Other information included in the metadata 204 may be metadata for use by business intelligence tools, text description of data contained in the table, keywords associated with the table to facilitate searching, a link (e.g., URL) to documentation related to the shared data, and a refresh interval indicating how frequently the shared data is updated along with the date the data was last updated ¶ [0041]. Also see ¶ [0034], [0058], [0131]).
It would have been obvious to one ordinary skilled in the art at the time of the present invention to combine the teachings of the cited references because Glickman’s system would have allowed Miller and, Munemann to facilitate generating a data dictionary for each of a set of data listings in a data exchange of a cloud computing platform, the data dictionary for each of the set of data listings comprising: first metadata describing data shared by a data listing; and second metadata describing individual objects included in the data shared by the data listing including tables, schemas, views, and functions. The motivation to combine is apparent in the Miller and, Munemann’s reference, because there need to improve resource management systems and methods that manage data storage and computing resources resource management systems and methods that manage data storage and computing resources.
Regarding claims 2, 9 and 16, the combination of Miller, Munemann and Glickman discloses, further comprising:
determining logical, semantic (Miller [0033]: In addition, an alternative search box 660 may be provided along with a drop down box of suggested alternative searches that are semantically similar to the query presented), and topic-related equivalences for each of the set of search terms (Miller [0034]: In addition, the topic nodes 424 are similarly colored with respect to one another, but differently colored from the query term nodes 422 such that a user can quickly discern whether a particular node is a query term node 422 or a topic node 424.);
generating a second query using the logical, semantic, and topic-related equivalences for each of the set of search terms; and processing the second query to retrieve additional data listings (Miller [0008]: The present invention provides a method including receiving a data stream, the data stream being a two-part torrent stream, wherein a first part of the two-part torrent stream 1s a torrent stream containing a first selection associated with a first result of a first query a second part is torrent stream containing updates io data contained in the first stream: identifying relevancy indicia associated with the selection; determining one or more refines associated with the relevancy indicia; and transmitting a second result of a second query, based at least in part on the first query and the one or more refines).
Regarding claims 3, 10 and 17, the combination of Miller, Munemann and Glickman discloses, wherein the set of listing -specific signals comprise one or more of: a term frequency-inverse document frequency (TF-IDF) of each of the set of search terms within a data listing, a distance of search terms from each other within the data listing, data characteristics of the data listing, or a lexical diversity of the data listing (Munemann: [0073]: Once one or more groups of related websites have been identified. Respective description data 132 or lexicon data associated with cack of the websites may be accessed from memory 328 or obtained from any number of data sources or other components of the architecture 100. Any number of suitable information extraction techniques and/or evaluation techniques, such as latent semantic analysis (“LSA”), heuristic information extraction algorithms (e.g., a term frequency-inverse document frequency (“TF-IDF”) analysis, etc.) and/or data-driven information extraction algorithms, may then be utilized to evaluate the description information 338 or the related tag data. In certain embodiments, one or more terms and/or phrases included in the description data 132 for a website or in relation to a user group may be weighted for purposes of determining keywords for the item. Additionally, one or more identifiers may be located and utilized to identify certain words and/or phrases to be weighted. For example, when evaluating a movie, terms and/or phrases that specify a genre for the movie may be weighted. Similarly, when evaluating an apparel item, terms and/or phrases that specify, define, or describe a style for the item may be weighted).
Regarding claims 4, 11 and 18, , the combination of Miller, Munemann and Glickman discloses, wherein the set of external signals comprise one or more of: a popularity score of a data listing, a click-through rate of the data listing, account specific data corresponding to an account that issued the query, and user-specific data of a user that issued the query (Munemann [0078]: In certain embodiments, the suggestion module 336 may be configured to generate suggestion based at least in part upon identified keywords tags or a similar lexicon. As desired, the suggestion module 336 may also utilize a purchase history or other historical information during the generation of suggestion. For example, the suggestion module 336 may be configured to provide a suggestion (i.e., a list of similar items, a topic that the user 102 may be interested in, etc.) to a user 102 in response to an action or event. In other examples, the suggestion may be a general suggestion based on habits, likes, or past purchases, or other historical and/or aggregated information regarding the user 102.)
Regarding claims 5, 12 and 19, the combination of Miller, Munemann and Glickman discloses, further comprising: receiving, from a browser, a request to load a web page corresponding to the data exchange in which the set of data listings id hosted (Munemann [0055]: In addition to monitoring user provided tags, the user application 306 may provide interaction data and find related or associated users. In some examples, the website 106 may host a social networking platform for interacting with other users and/or sharing items. Based on these communication patterns or social networking connections, the user application 306 may determine related users in various contexts); and
providing to the browser, as part of the web page, logic for generating the set of listing-specific signals and the set of external signals (Munemann [0087]: The user-defined lexicon data 216 may be stored. This may include semantic data 216(1), negative filter data 216(2), ratings data 216(3), or a combination thereof. The semantic data 216(1) may include a special designation, definitions, identification, mark, term, symbol, text, sound, image or other multimedia. The semantic data 216(1) may identify one or more terms and associations for search results. The negative filter data may also include exclusionary information regarding special designations, definitions, identification, mark, term, symbol, text, sound image or other multimedia. The ratings data 216(3) may include descriptions, characteristics, rankings, terms of use, and so forth).
Regarding claims 6, 13 and 20, the combination of Miller, Munemann and Glickman discloses, wherein the processing device is further to: present a description of each listing of the set of data listings (Glickman: A listing 202 may include metadata 204 describing the shared data. The metadata 204 may include some or all of the following information: an identifier of the sharer of the shared data, a URL associated with the sharer, a name of the share, a name of tables, a category to which the shared data belongs, an update frequency of the shared data, a catalog of the tables, a number of columns and a number of rows in each table, as well as name for the columns ¶ [0041]. Also see ¶ [0055], [0069]).
Regarding claims 7, and 14, the combination of Miller, Munemann and Glickman discloses, wherein to generate the set of listing-specific signals and the set of external signals, the processing device is to analyze the data dictionary for each of the set of data listings (Miller [0033]: Referring to FIG. 4, the graphical user interface 400 includes a natural language query input element 410, a query visualization and manipulation element 420, a results feedback element 430, and a results listing element 440. The natural language query input element 410 is configured to request a submission of a natural language search query from a user. In some embodiments, text input may be provided in the natural language query input element 410, such as when a user can select the natural language query input element 410 as a field of entry and type text into the natural language query input element 410).
Conclusion
The examiner requests, in response to this Office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line no(s) in the specification and/or drawing figure(s). This will assist the examiner in prosecuting the application.
When responding to this office action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections See 37 CFR 1.111(c).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMAD S ROSTAMI whose telephone number is (571)270-1980. The examiner can normally be reached Mon-Fri From 9 a.m. to 5 p.m..
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12/19/2025
/MOHAMMAD S ROSTAMI/Primary Examiner, Art Unit 2154