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 .
This communication is in response to application 18/057,357 filed on 11/21/2022. Claims 1-20 are pending and hereby examined. No claims are allowed.
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 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) with no practical application and without significantly more.
The claimed invention is directed to an abstract idea in that the instant application is directed to a mental process (See MPEP 2106.04(a)(2)(III)). The independent claims (1, 8, and 15) recite a method and systems that collect collaboration data to create modules based on analyzed data. Further the claim also recites generating a word cloud. These claim elements are being interpreted as mental processes. For example, collection and analysis of data can be done by a human to create a word cloud. Further, the generated modules are claimed so broadly they amount to groups of data that have been collected and analyzed; therefore, the claims recite an abstract idea consistent with the “mental process” grouping set forth in the MPEP 2106.04(a)(2)(III).
Additionally, the claimed invention is directed to an abstract idea in that the instant application is directed to certain methods of organizing human activities (see MPEP(a)(2)(II)). The independent claims recite a method and systems that represent a user in a virtual collaboration. This claim element is being interpreted as managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). Representing a person in a meeting involves relationships and interactions between people; therefore, the claims recite an abstract idea consistent with certain methods of organizing human activity grouping set forth in the MPEP(a)(2)(II).
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites an “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea. The instant application is directed towards a method and systems to implement the identified abstract ideas of a mental process and certain methods of organizing human activity in a general-purpose computer environment. The independent claims recite the additional elements “one or more processors”, “one or more computer-readable tangible storage medium”, and “a non-transitory computer-readable storage media”. These claim elements are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a general computer environment. The machines merely act as a modality to implement the abstract idea and are not indicative of integration into a practical application (i.e., the additional elements are simply used as a tool to perform the abstract idea), see MPEP 2106.05(f).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed in Step 2A Prong Two analysis, the additional elements in the claims amount to no more than mere instructions to apply the exception using general purpose computing components. The same analysis applies here in 2B and does not provide an inventive concept.
Regarding the dependent claims:
Claims 5, 12, and 19 introduce the new additional element “skip-gram model”. However, the model is not indicative of integration into a practical application. It is described at such a high level of generality that it amounts to no more than a tool to perform the abstract idea, see MPEP 2106.05(f).
Claims 2-4, 6-7, 9-11, 13-14, 16-18, and 20 do not introduce any new additional elements or new abstract ideas and do not impact analysis under 35 USC 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (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 1-4, 6-11, and 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over Adlersberg (US 20200279567 A1) in view of Cai (US 20190349321 A1).
Regarding Claims 1, 8, and 15, Adlersberg teaches:
A computer system for enabling virtual collaboration representation, comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising: [see at least Adlersberg: (Para 0062) “Some embodiments may comprise a non-transitory storage medium having stored thereon instructions that, when executed by a hardware processor, cause the hardware processor to perform a method as described above.”]
A computer program product for enabling virtual collaboration representation, comprising: one or more non-transitory computer-readable storage media and program instructions stored on at least one of the one or more tangible storage media, the program instructions executable by a processor to cause the processor to perform a method comprising: [see at least Adlersberg: (Para 0134) “The present invention may be implemented by using code or program code or machine-readable instructions or machine-readable code, which is stored on a non-transitory storage medium or non-transitory storage article (e.g., a CD-ROM, a DVD-ROM, a physical memory unit, a physical storage unit), such that the program or code or instructions, when executed by a processor or a machine or a computer, cause such device to perform a method in accordance with the present invention”]
A method for enabling virtual collaboration representation, the method comprising:
receiving a virtual collaboration history; [see at least Adlersberg: (Para 0021) “The captured audio/video data may be stored in a Meeting Data Repository 104. Additionally or alternatively, such audio and/or video may be received from an external source, such as, from a tele-conferencing service that is operated by a third party; for example, a Meeting Audio/Video Receiver 105 may receive audio/video of such meeting from the external source or from the third-party, and may store it (in its original format, or after being reformatted) in the Meeting Data Repository 104.”]
generating a first module, wherein the first module is generated based on an analysis of the virtual collaboration history; [see at least Adlersberg: (Para 0039) “further generate insights with regard to related meetings correlation (e.g., recurrent, events) performance metrics. For example, the system may analyze and generate insights with regard to recurrent meeting AI execution time (e.g., or other performance metrics); and may indicate, for example, that current and/or previous AI execution time for a previously-processed meeting”]
receiving a virtual collaboration invite and generating a second module based on the virtual collaboration invite; [see at least Adlersberg: (Para 0107) “For example, an Agenda Extraction and Monitoring Unit 164 may operate to extract or obtain the agenda of topics for this particular meeting; for example, by extracting topics from an Invitation to the meeting as sent to participants”]
monitoring a virtual collaboration; [see at least Adlersberg: (Para 0096) “ For example, as demonstrated in FIG. 1, a computerized or automated MMB 160 may be part of system 100, and may monitor the audio uttered or spoken by the various participants in the meeting”]
However, Adlersberg does not teach but Cai does teach:
generating a word cloud; and [see at least Cai: (Para 0146) “As another example, the natural language processor 120 can generate a term-frequency word Cloud/bar chart. See for example, FIG. 5. The word cloud and the term-frequency bar chart can provide a glimpse into the top key words that are being discussed in the document. The size of the words are determined by the amount of times the word appears in the document.”]
representing a user in the virtual collaboration using a proxy bot, wherein the proxy bot leverages the word cloud. [see at least Cai: (Para 0046) “The virtual agent 180 (chat bot) that can interact with the communication platform users. The virtual agent 180 (chat bot) can provide a flexible user experience with cognitive natural language interaction”, (Para 0183) “The virtual agent 180 can implement a “chatbot” to provide output based on predictive/prescriptive model 126. The virtual agent 180 can integrate with natural language processor 120 for text analysis and summary report generation.”]
Further, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine meeting information monitoring (Adlersberg) with the generation of a word cloud and representation with a bot (Cai). One of ordinary skill would have recognized that using meeting information to develop a word cloud and bot would create to a more adaptable bot for virtual collaboration. The invention is merely a combination of old elements and in combination each element would have performed the same function as it did separately, yielding predictable results.
Regarding Claims 2, 9, and 16, the combination of Adlersberg and Cai teach the limitations of claim 1. Adlersberg further teaches:
wherein receiving the virtual collaboration history further comprises: creating one or more virtual collaboration groupings. [see at least Adlersberg: (Para 0016) “Such data may be automatically generated and organized in a searchable format, which enables the organization or users to later retrieve and search through the data”]
Regarding Claims 3, 10, and 17, the combination of Adlersberg and Cai teach the limitations of claim 1. Adlersberg further teaches:
wherein the first module is generated using one or more linguistic analysis techniques. [see at least Adlersberg: (Para 0024) “a Natural Language Processing (NLP) unit 108 may perform initial analysis or the transcript”]
Regarding Claims 4, 11, and 18, the combination of Adlersberg and Cai teach the limitations of claim 1. Adlersberg further teaches:
wherein monitoring the virtual collaboration further comprises: generating a third module, wherein the third module is generated using one or more neural networks. [see at least Adlersberg: (Para 0066) “performing a string analysis using NLP algorithms and/or textual analysis and/or contextual analysis”]
Regarding Claims 6, 13, and 20, the combination of Adlersberg and Cai teach the limitations of claim 1. Adlersberg further teaches:
using at least the first module, [see at least Adlersberg: (Para 0039) “For example, the system may analyze and generate insights with regard to recurrent meeting AI execution time (e.g., or other performance metrics); and may indicate, for example, that current and/or previous AI execution time for a previously-processed meeting and/or for a currently-processed meeting;”]
the second module, [see at least Adlersberg: (Para 0107) “For example, an Agenda Extraction and Monitoring Unit 164 may operate to extract or obtain the agenda of topics for this particular meeting; for example, by extracting topics from an Invitation to the meeting as sent to participants”]
and a third module [see at least Adlersberg: (Para 0066) “performing a string analysis using NLP algorithms and/or textual analysis and/or contextual analysis”]
However, Adlersberg does not teach but Cai does teach:
wherein the word cloud is generated [see at least Cai: (Para 0146) “As another example, the natural language processor 120 can generate a term-frequency word Cloud/bar chart. See for example, FIG. 5. The word cloud and the term-frequency bar chart can provide a glimpse into the top key words that are being discussed in the document. The size of the words are determined by the amount of times the word appears in the document.”]
Further, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use historical data, invitation data, and analysis (Adlersberg) to generate a word cloud (Cai). One of ordinary skill would have recognized using collaboration information to generate a word cloud would create a more meeting relevant corpus of data. The invention is merely a combination of old elements and in combination each element would have performed the same function as it did separately, yielding predictable results.
Regarding Claims 7 and 14, the combination of Adlersberg and Cai teach the limitations of claim 1. Adlersberg further teaches:
wherein the user is represented in the virtual collaboration according to one or more options selected by the user in a user interface. [See at least Adlersberg: (Para 0112) “Specifically, user Adam may invite to the meeting an “MMB” invitee or service, as a Meeting Moderator Bot which may be pre-defined on the system”]
Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Adlersberg (US 20200279567 A1) in view of Cai (US 20190349321 A1) in further view of Jwala (Developing a Chatbot using Machine Learning).
Regarding Claims 5, 12, and 19, the combination of Adlersberg and Cai teach the limitations of claim 4. While the combination teaches generating a module with a neural network, it does not explicitly teach a skip-gram model.
However, Jwala teaches:
wherein the third module is a skip-gram model. [see at least Jwala: (Page 91, Column 2) “Word2vec combines two models called CBOW (Continuous bag of words) and Skip-gram. These are shallow neural networks. For each word(s) in the vocabulary of training corpus, they learn weights that show the association between the word(s) and other words in the training corpus. These weights act as word vector representations.”]
Further, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the generation of the module (Adlersberg and Cai) with the use of a skip-gram model (Jwala). Simple substitution of the NLP techniques used in the combination of Adlersberg and Cai with another NLP technique discussed in Jwala would produce a predictable result, rendering the claim obvious.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Examiner Benjamin Truong, whose telephone number is 703-756-5883. The examiner can normally be reached on Monday-Friday from 9 am to 5 pm (EST)
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/B.L.T./
Examiner, Art Unit 3626
/NATHAN C UBER/Supervisory Patent Examiner, Art Unit 3626