DETAILED ACTION
This communication is in response to the after-final amendment filed 7/1/26 in which claims 1, 10, and 19 were amended. Claims 1-20 are pending.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/1/26 has been entered.
Response to Arguments
Applicant’s arguments with respect to claims 1, 10, and 19 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 1-3, 5, 10-12, 14, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Summers (US 2010/0031141 A1; published Feb. 4, 2010) in view of Harshika, Hettiarachchige Dona Nidhana, et al. "Toward Extracting and Predicting Instance-Specific Attribute Values from E-Commerce Sites for Used Products." 2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2016 (“Harshika”) and Sandhu (US 2014/0324808 A1; published Oct. 30, 2014).
Regarding claim 1, Summers discloses [a] method for aggregating related documents, the method comprising:
accessing, by a processor and based on receiving an attribute associated with aggregating related documents, a plurality of electronic documents; (Summers ¶ 27 (“A more detailed view of the dynamic processor is illustrated in FIG. 2. A request for information is presented to the API 12, for example via a browser. This request, in the form of query, can be of a variety of different types. For example, one type of query might request a particular item of data for a number of different companies, e.g., annual revenue for all companies in the beverage industry. Another type of query may request all data for a given company of interest, or data over a particular time span, such as the ten-year revenue growth for a particular company. The API presents these requests to the dynamic processor 14, for example, in the form of a function call with parameters that identify the particular items of interest in the request.”), ¶ 28 (“The dynamic processor contains a number of pre-fabricated algorithms that are executed by an algorithm manager 28. Each algorithm is designed to retrieve information in response to a particular type of request. In essence, each algorithm implements a particular type of search strategy. For example, one algorithm can function to retrieve all items from a collection of documents, e.g., all data relating to a particular company. Another algorithm can function to retrieve the metadata associated with a particular fact.”))
executing a trained machine learning model to generate, based on the received attribute as an input to the trained machine learning model and for each of the plurality of electronic documents, a plurality of values, a plurality of categories, a plurality of sub-categories, and a location within a corresponding electronic document for each of the plurality of values, wherein each of the plurality of values corresponds to a category and a sub-category related to a content of a text or an associated metadata of the plurality of electronic documents; (Summers ¶ 54 (“Upon receiving a command to convert the uploaded document, a converter application executing in the server 42 sections the document into different components. The user selects one or more sections, and the application then provides an initial classification of a section by parsing the content of the section and assigning a concept to each identifiable fact item that is detected during the parsing. The classified fact items are then forwarded to the user's local computer 40 for review and correction.”), ¶ 55 (“The converter application automatically identifies and classifies the fact items. The results of this process improve by virtue of an iterative learning process. At first, the converter application may not have any knowledge base from which to identify and/or classify fact items, and therefore might not return any identified facts to the user or suggest a classification for them. Once the user reviews and revises, or adds, classifications to facts, the correctly labeled facts are forwarded to the converter application for training purposes. For example, the application might operate in the manner of a Bayes classifier to determine the most likely concept for an identified fact, based upon its content and its context within the document. When the corrected facts are forwarded to the converter application, it can employ the information provided by the user to update the probabilities that various respective concepts might be associated with a given fact item. The next time a document is presented for classification, the classifier can utilize these updated probabilities to provide suggested labels for at least some of the identified fact items in that document.”)).
Summers does not expressly disclose:
identifying, by the processor and from the plurality of electronic documents, a subset of the plurality of electronic documents, wherein each of the subset of the plurality of electronic documents is associated with at least one of the plurality of values and the at least one of the plurality of values is different than the received attribute; and (but see Harshika Section 3.4 (“As shown on Figure 8, users can view only descriptions [e.g., plurality of electronic documents], which have been supplied by the sellers, about the used iPhone [e.g., received attribute]. If the user is interested about a significant characteristic about a used iPhone, then the user may search and see information about other phones, descriptions, which as well. By using our system, if a user seeks about some significant characteristics on the phone, the user just input some keyword on our interface, as shown in Figure 9. If the seller provided lots of unnecessary details about a used product then using our interface user can simply find the significant characteristics when looking for phones, without reading every words on the description. The user can see the predicted missing significant specifications which the user is looking for the product as well. Example: If the seller did not mention about the attribute value of “UNLOCKED”, Our system will give a predicted value about the attribute “UNLOCKED” on the Phone. This will help user on make their buying decisions.”)
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(Figure 8 is a listing of two product descriptions as originally provided by the sellers)
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(Figure 9 is the output after a user searches for a used iPhone with specific attribute values/keywords (unlocked imei) [plurality of values] that are generated by the system predicting missing specification values not found in the original descriptions provided by the sellers. The search results in Figure 9 are more narrowly drawn [e.g., subset of the plurality of electronic documents] than the results in Figure 8 with the original descriptions.)
generating, by the processor, a graphical user interface including: (but see Harshika Figure 9)
a first portion displaying a portion of each of the subset of the plurality of electronic documents… (but see Harshika Figure 9 graphical user interface shows a listing of products being sold on Amazon (e.g., first item description “Factory unlocked for any GSM provider with a SIM card. Shows some…,” third item description “Tested and fully functional. Includes generic charger and USB cable. 30 day warranty”)
a second portion displaying one or more of the plurality of values common to the subset of the plurality of electronic documents (but see Harshika Figure 9 the graphical user interface also displays the keywords input by the user that were used to find the items and their predicted values (e.g., “unlocked: Yes,” “imei: Yes”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Summers to incorporate the teachings of Harshika to generate a user interface for the search and display a subset of specific content in a category of content, at least because doing so would automatically extract and predict attribute values that the user may be interested in. See Harshika Section 1.
Summers and Harshika fail to expressly disclose that the first portion displays a portion of each of the documents corresponding to the location within the subset of the plurality of electronic documents (but see Sandhu FIG. 12, ¶ 88 (“In another embodiment of this invention the user is also provided a method of automatically seeing the relevant word segments from various parts of the patent specification. The user is given an ability to select any specific word or tag. FIG. 12 shows a user interface of semantic-segmentation based search model displaying claim segments with active links—pop up specification references and their referred figures, in accordance with an embodiment of the present invention. The method provides a way to show a pop-up display 1204 that shows relevant sections from the patent specification that maps to the selected word or tag. In another embodiment, the user may hover with the mouse or other selector on the segment of interest and the specification quote may automatically pop-up. In another embodiment, the user may right click, left click, or otherwise perform an action on the segment to have the specification quote pop up.”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Summers to incorporate the teachings of Sandhu to display a portion of the text that map to a selected word or tag, at least because doing so would provide the user a way of automatically seeing the relevant words segments from various parts of the documents.
Claim 10 is a system claim corresponding to claim 1 and is similarly rejected. Summers further discloses [a] system for aggregating related documents, the system comprising: a processor; and a memory comprising instructions that, when executed, cause the processor to: (FIG. 8 (server 42 includes a processor and memory with instructions to perform the methods)).
Claim 19 is a computer-readable medium claim corresponding to claim 1 and is similarly rejected. Summers further discloses [o]ne or more non-transitory computer-readable storage media storing computer-executable instructions for performing a computer process on a computing system, the computer process comprising: (¶ 80 (“As a third implementation, the data processor might be a web-based application executing on a server that a user accesses through a suitable browser. In each case, the software components that constitute the API and the dynamic processor are encoded on a computer-readable medium that is accessed by the supporting server and/or desktop computer.”)).
Regarding claim 2, Summers, in view of Harshika and Sandhu, discloses the invention of claim 1 as discussed above. Summers et al. do not expressly disclose wherein the attribute is selected from one of a company name, an agreement number, an agreement type, an agreement status, an expiration date, an activation date, or an auto-renewal status (but see Harshika Figure 5 (description includes items such as product status and a 30 day warranty)).
Summers is combinable with Harshika for the same reasons as set forth above.
Claim 11 is a system claim corresponding to claim 2 and is similarly rejected.
Claim 20 is a computer-readable medium claim corresponding to claim 2 and is similarly rejected.
Regarding claim 3, Summers, in view of Harshika and Sandhu, discloses the invention of claim 1 as discussed above. Summers et al. do not expressly disclose wherein the graphical user interface further includes a third portion displaying the plurality of values associated with a selected one electronic document of the subset of the plurality of electronic documents (but see Harshika Figure 9 (the right side of the interface includes delivery details for each product listing).
Summers is combinable with Harshika for the same reasons as set forth above.
Claim 12 is a system claim corresponding to claim 3 and is similarly rejected.
Regarding claim 5, Summers, in view of Harshika and Sandhu, discloses the invention of claim 1 as discussed above. Summers does not expressly disclose wherein displaying the one or more of the plurality of values common to the subset of the plurality of electronic documents is based on a selection of the one or more of the plurality of values via the graphical user interface (but see Harshika Figure 9 (user selects the ‘ok’ button to select the keywords “unlocked imei” entered by the user)).
Summers is combinable with Harshika for the same reasons as set forth above.
Claim 14 is a system claim corresponding to claim 5 and is similarly rejected.
Claims 4 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Summers, Harshika, and Sandhu as applied to claims 1 and 10 above, and further in view of Angell (US 2007/0112748 A1; published May 17, 2007).
Regarding claim 4, Summers, in view of Harshika and Sandhu, discloses the invention of claim 1 as discussed above. Summers does not expressly disclose adding a second subset of the plurality of electronic documents to the subset of the plurality of electronic documents based on the second subset of the plurality of electronic documents being associated with the one or more of the plurality of values common to the subset of the plurality of electronic documents (but see Angell Abstract (“A system and method for processing a document to generate a set of related documents. A system is provided that includes a textual analytics system that analyzes unstructured data contained in a source document and extracts a set of structured information about the source document; and a compare system that identifies a set of related documents by comparing the set of structured information with metadata indexed from a set of publications.”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Summers and Harshika to incorporate the teachings of Angell to analyze the subset of web content obtained by predicting missing attribute values to generate an additional subset of related documents by comparing the structured information with metadata indexed from a set of publications, at least because doing so would allow a user to find related web content without relying on explicit search terms. See Angell ¶ 12.
Claim 13 is a system claim corresponding to claim 4 and is similarly rejected.
Claims 7, 8, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Summers, Harshika, and Sandhu as applied to claims 1 and 10 above, and further in view of Blanco (US 2013/0159222 A1; published Jun. 20, 2013).
Regarding claim 7, Summers, in view of Harshika and Sandhu, discloses the invention of claim 1 as discussed above. Summers and Harshika do not expressly disclose wherein a first of the plurality of values of a first electronic document conflicts with a second of the plurality of values of a second electronic document, the graphical user interface further including an indication of the conflict between the first electronic document and the second electronic document (but see Blanco ¶ 54 (“FIG. 6 shows an example of an object search result with duplication in attribute values. The value for the predicate "http://dbpedia.org/property/date" appears in the data as both 2008-07-24 (object 610) and 2008 Jul. 24 (object 620). After dragging and dropping one key/value pair over the other, the user is prompted with the screen 700 shown in FIG. 7, where he/she can choose which value to keep (which value will be displayed). In this example the user has selected 2008-07-24 (object 610 from FIG. 6) by clicking on the button associated with this value. Other means of selection, such as checkmarks, highlighting, and the like are also contemplated within the spirit and scope of the invention. Note that although in this particular case the two values are semantically equivalent, the properties could have different values, which could be either conflicting or valid alternatives.”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Summers and Harshika to incorporate the teachings of Blanco to indicate duplication/conflict in search results and allowing the user to select a version of the results, at least because doing so would enable disambiguation and editorial curation of data in web documents. See Blanco ¶ 36.
Claim 16 is a system claim corresponding to claim 7 and is similarly rejected.
Regarding claim 8, Summers, in view of Harshika and Sandhu, discloses the invention of claim 7 as discussed above. Summers and Harshika do not expressly disclose: selecting a controlling version for the conflict between the first electronic document and the second electronic document; (but see Blanco (US 2013/0159222 A1; published Jun. 20, 2013) ¶ 54 (“FIG. 6 shows an example of an object search result with duplication in attribute values. The value for the predicate "http://dbpedia.org/property/date" appears in the data as both 2008-07-24 (object 610) and 2008 Jul. 24 (object 620). After dragging and dropping one key/value pair over the other, the user is prompted with the screen 700 shown in FIG. 7, where he/she can choose which value to keep (which value will be displayed). In this example the user has selected 2008-07-24 (object 610 from FIG. 6) by clicking on the button associated with this value. Other means of selection, such as checkmarks, highlighting, and the like are also contemplated within the spirit and scope of the invention. Note that although in this particular case the two values are semantically equivalent, the properties could have different values, which could be either conflicting or valid alternatives.”))
and automatically editing, via the trained machine learning model, at least one of the subset of the plurality of electronic documents to include the controlling version (but see Blanco ¶ 45 (“Automated learning will improve search engine results. The system may use the information provided by the user to learn the automated disambiguation of triples and objects using machine-learning techniques. A number of machine learning methods exist in the literature under the name `record linkage` that allow the matching of objects and triples based on training data obtained from users. These models may be learned for each user separately from the data collected from only that user or for the collective of users from the data collected in aggregate.”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Summers and Harshika to incorporate the teachings of Blanco to indicate duplication/conflict in search results and allowing the user to select a version of the results, at least because doing so would enable disambiguation and editorial curation of data in web documents. See Blanco ¶ 36.
Claim 17 is a system claim corresponding to claim 8 and is similarly rejected.
Claims 6, 9, 15, 18 are rejected under 35 U.S.C. 103 as being unpatentable over Summers, Harshika, and Sandhu as applied to claims 1 and 10 above, and further in view of Dahl (US 2015/0066976 A1; published Mar. 5, 2015).
Regarding claim 6, Summers, in view of Harshika and Sandhu, discloses the invention of claim 1 as discussed above. Summers and Harshika do not expressly disclose:
wherein the received attribute is a paragraph, (but see Dahl ¶ 17 (“Recurring text identification service 102 may be configured to partition individual documents of documents 108 into segments to be processed. For example, recurring text identification service 102 may partition the individual documents based upon paragraph break indicators, such as carriage returns and/or line feeds. Recurring text identification module 102 may be further configured to analyze each segment and generate a content based identifier associated with the segment.”)) the method further comprising:
converting, by the processor and via a hashing technique, the paragraph to a hashed value, the at least one of the plurality of values comprising the hashed value (but see Dahl ¶ 18 (“The content based identifier may be unique to the content contained within the segment, such that any segment having the same content based identifier may contain the same content. In embodiments, the content based identifier may be generated by applying a hash function to the content of the segment, such as that depicted in FIG. 2. In embodiments, recurring text identification service 102 may be configured to generate a recurring text report 118 utilizing the content based identifiers for output.”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Summers and Harshika to incorporate the teachings of Dahl to apply a hash function to the content of a paragraph in a record, at least because doing so would allow deduplication of duplicate records without manual inspection of each record.
Claim 15 is a system claim corresponding to claim 6 and is similarly rejected.
Regarding claim 9, Summers, in view of Harshika and Sandhu, discloses the invention of claim 1 as discussed above. Summers and Harshika do not expressly disclose wherein the electronic document is received as an image file and converted to a text format using optical character recognition software (but see Dahl ¶ 15 (“In some embodiments documents 108 may contain images of documents that may have no associated text. In such embodiments it may be necessary to perform an OCR process on the image of the document to extract text from the image. As depicted here, recurring text identification service 102 may send request 124 to OCR module 106 containing document images or links to document images for OCR module 106 to process. OCR module 106 may be configured to process each document image of request 124 and extract associated text from each document image.”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Summers to incorporate the teachings of Dahl to apply a hash function to the content of a paragraph in a record, at least because doing so would allow deduplication of duplicate records without manual inspection of each record.
Claim 18 is a system claim corresponding to claim 9 and is similarly rejected.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAHID KHAN whose telephone number is (571)270-0419. The examiner can normally be reached M-F, 9-5 est.
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/SHAHID K KHAN/Primary Examiner, Art Unit 2146
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