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
This action is in reply to the preliminary amendment filed on 26 April 2024.
Claim 1 has been amended.
Claims 2-20 have been added.
Claims 1-20 are currently pending and have been examined.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7 May 2024 was filed after the mailing date of the initial disclosure but prior to any action on the merits. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 an abstract idea without significantly more.
The claims recite, as a whole, a method of organizing human activity because the claim recites a method that builds or updates supplier provides from gathered data including keywords, tags and determined sentiments in order to source suppliers or vendors. This is a commercial interaction since it relates to advertising, marketing or sales activities or behaviors and business relations. The mere nominal recitation of a generic processor coupled to a storage media and functional modules executable to perform the steps does not take the claims out of the methods of organizing human activities grouping. Thus, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. The claims as a whole merely describe how to generally apply the concept of accessing and storing data, determining sentiments and building a searchable profile in a computer environment or platform. The claimed computer components are recited at a high level of generality and are merely invoked as tools to perform a data gathering, determination and profiling process for sourcing vendors. Simply implementing the abstract idea in a generic computer environment or processor with functional modules is not a practical application of the abstract idea. Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application and the claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A, the claims as a whole merely describe how to generally apply the concept of building or updating a searchable profile from accessed data in a computer environment. Thus, even when viewed as a whole, nothing in the claims adds significantly more to the abstract idea.
Dependent Claims 2-10 and 12-20 include all of the limitations of the independent claims and therefore recite the same abstract idea. The claims merely narrow the recited commercial interaction by describing additional data mapping, options of using alternative tags, grouping similar businesses, summarizing data, determining capabilities and credibility or experience, updating the profile, providing suggestions and determining sentiments using machine learning techniques, which are simply computer based applications since no further details was provided and transmitting data. No additional elements are recited that transform the claim into a patent eligible invention but instead further describe the processes for sourcing vendors or suppliers applied by generically recited computer elements.
Therefore, claims 1-20 are ineligible as they are directed to an abstract idea without significantly more.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Subbloie (WO 00/30004) in view of DAVAR et al. (US 2016/0335603).
As per Claim 1 Subbloie teaches:
A procurement platform system, comprising: at least one processor coupled to at least one computer storage media; and a plurality of functional modules executable by the at least one processor to build and maintain a plurality of electronically stored and searchable supplier profiles, including at least one functional module executable to (Subbloie Pg. 4 and Fig. 1-3 illustrate a network accessible system comprising processor and medium with executable instructions):
build or update an electronically searchable supplier profile including the identified keywords, descriptions of the supplier's goods and/or services, and (Subbloie Fig. 5 item 118 illustrates the customer master file, Pg. 8 lines 5-15 describes storing consumer specific information, Pg. 19 describes the customer master file including name, address, preferences, history and profile, Fig. 5 item 114 illustrates the vendor attributes file, Pg. 9 lines 7-20 describes storing vendor specific information, Pg. 18 describes the vendor attributes files including general information, address, location, service levels, size, hours of operations, quality or service, etc.).
Subbloie does not explicitly recite that the profile includes extracted tags and determined sentiments which are automatically accessed from websites and online references materials. However,
automatically access a supplier website and online reference material related to the supplier to extract supplier information, including keywords and tags, and determine sentiments about the supplier, wherein the keywords and tags include words or phrases related to goods and/or services offered by the supplier (DAVAR in at least [0053] describes how processors are used to identify users who are registered on a social network as service providers, the processors then retrieve from the social network professional profile data of said users and generate and store a services model from features extracted from the professional profile data, Fig. 6 and at least [0030, 0043, 0101, 0107, 0120, 0143-0145, 0157] illustrate and describe the ability to identify content objects and content that can be tagged to identify particular information, such as endorsements which are used to compare tagged features to a service mode and receive a representation of services. DAVAR in at least [0017-0021] describe the ability to store and use response scores to evaluate actions of providers as positive or negative as well as review scores that can indicate a strength of connection which can all be considered sentiments because the scores are all determined values that represent a view or attitude).
Therefore, it would be obvious to one of ordinary skill in the art to modify the ability to build, update and store a supplier profile to include techniques for utilizing tags and sentiment for evaluating content from profiles because each of the elements were known, but not necessarily combined as claimed. The technical ability existed to combine the elements as claimed and the result of the combination is predictable because each of the elements performs the same function as it did individually. By utilizing tagged information and sentiments, such as endorsement in a profile in combination with keyword matching and service categories, the combination enables precise results to be generated based on a measure of truth and of the matching (DAVAR [0005-0006]).
As per Claim 2 Subbloie does not teach but DAVAR further teaches:
wherein the functional modules are further executable to map one or more of the keywords to alternative tags, wherein the alternative tags comprise words or phrases known to have similar meaning within the field of the supplier (DAVAR in at least [0101-0102 and 0125] describes mapping features found to profiles to services using rules and weightings and the ability to use a topic model to map features to different service nodes, [0043-0048] describes the ability to calculate similarity scores based on features in professional profiles of the users, [0156-0157] describes the social relevance agent that can identify content objects and calculate their relevance from tags or features and from similarity of profiles, see also [0032, 0042, 0090, 0109, 0117, 0128, 0145, 0152-0156 and Fig. 5 )
DAVAR is combined based on the reasons and rationale set forth in the rejection of Claim 1 above.
As per Claim 3 Subbloie does not explicitly recite but DAVAR further teaches:
wherein the functional modules are further executable to enable the supplier to selectively opt out of or include the alternative tags to in the supplier profile (DAVAR in at least [0122] describes predefined options that may be selection including sets of criteria options to display and subsequent criteria selection being used during a search of the services index to identify suitable providers).
DAVAR is combined based on the reasons and rationale set forth in the rejection of Claim 1 above.
As per Claim 4 Subbloie does not teach but DAVAR further teaches:
wherein the functional modules are further executable to map the supplier profile into a grouping of suppliers in similar lines of business (DAVAR in at least [0101-0102 and 0125] describes mapping features found to profiles to services using rules and weightings and the ability to use a topic model to map features to different service nodes, [0043-0048] describes the ability to calculate similarity scores based on features in professional profiles of the users, [0156-0157] describes the social relevance agent that can identify content objects and calculate their relevance from tags or features and from similarity of profiles, see also [0032, 0042, 0090, 0109, 0117, 0128, 0145, 0152-0156 and Fig. 5 )
DAVAR is combined based on the reasons and rationale set forth in the rejection of Claim 1 above.
As per Claim 5 Subbloie does not teach but DAVAR further teaches:
wherein the functional modules are further executable to generate a summary of supplier capabilities from the extracted supplier information and include the summary within the supplier profile (DAVAR in at least [0105-0107] describes generating summary data from provider or supplier information).
DAVAR is combined based on the reasons and rationale set forth in the rejection of Claim 1 above.
As per Claim 6 Subbloie does not teach but DAVAR further teaches:
wherein the functional modules are further executable to determine a credibility and/or level of experience of the supplier for each supplier capability (DAVAR in at least [0027] describes the service model as being able to estimate and judge providers based on experience, skills, education, etc.).
DAVAR is combined based on the reasons and rationale set forth in the rejection of Claim 1 above.
As per Claim 7 Subbloie further teaches:
wherein the functional modules are further executable to enable the supplier to electronically update the supplier profile (Subbloie Fig. 3 describes techniques for updating product and service data generated by a vendor in the system, Fig. 5 item 118 illustrates the customer master file, Pg. 8 lines 5-15 describes storing consumer specific information, Pg. 19 describes the customer master file including name, address, preferences, history and profile, Fig. 5 item 114 illustrates the vendor attributes file, Pg. 9 lines 7-20 describes storing vendor specific information, Pg. 18 describes the vendor attributes files including general information, address, location, service levels, size, hours of operations, quality or service, etc., Figs. 7A-B illustrate and describe updating files stored either daily or by other suitable techniques).
As per Claim 8 Subbloie further teaches:
wherein the functional modules are further executable to provide automated suggestions to the supplier to assist the supplier in categorizing its goods and/or service offerings (Subbloie Fig. 5 illustrates and describes the product matching system that includes the ability to recommend given products based on attributes of their choosing, Fig. 7A-C illustrates listing the various recommendations, Pg. 10 lines 16-19 describes the processing system responding with a list of vendors for the selected categories matching the requested information keywords, e.g. a list of candidate suppliers matching the input requirements, as is further described in at least Pg. 20, 22).
As per Claim 9 Subbloie does not teach but DAVAR further teaches:
wherein the functional modules are further executable to use machine-learning techniques to evaluate the reference material to determine the sentiments of the supplier and extract information about the capabilities and/or reputation of the supplier, including identifying positive and/or negative views about the supplier and/or the supplier's goods and/or services (DAVAR in at least [0053] describes how processors are used to identify users who are registered on a social network as service providers, the processors then retrieve from the social network professional profile data of said users and generate and store a services model from features extracted from the professional profile data, Fig. 6 and at least [0030, 0043, 0101-0103, 0107, 0120, 0126 0143-0145, 0157] illustrate and describe the ability to identify content objects and content that can be tagged to identify particular information, such as endorsements which are used to compare tagged features to a service mode and receive a representation of services and feeding that data into a learning model for classification and using machine learning for analysis, DAVAR in at least [0017-0021] describe the ability to store and use response scores to evaluate actions of providers as positive or negative as well as review scores that can indicate a strength of connection which can all be considered sentiments because the scores are all determined values that represent a view or attitude.
DAVAR is combined based on the reasons and rationale set forth in the rejection of Claim 1 above.
As per Claim 10 Subbloie further teaches:
wherein the functional modules are further executable to transmit an electronic invitation to the supplier to create and/or update the supplier profile (Subbloie in at least Fig. 5 and its associated text illustrate and describe a configuration wizard that may be provide that will provide a vendor with the ability to associate products with attributes in a template, wizards are also described as being utilized with templates or other forms that may be maintained by the vendors to implement global changes or other data, pgs. 17-20)
As per Claims 11-20 the limitations are substantially similar to those set forth in Claims 1-10 and are therefore rejected based on the same reasons and rationale set forth in the rejections of Claims 1-10 above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEPHANIE Z DELICH whose telephone number is (571)270-1288. The examiner can normally be reached on Monday - Friday 7-3:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao Wu can be reached on 571-272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/STEPHANIE Z DELICH/Primary Examiner, Art Unit 3623
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