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 .
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 the
abstract idea of a mental process, as it represents concepts that can be performed in human mind
(including observations, evaluations, and judgements), and/or certain methods of organizing
human activity, as it seeks to keep track of different communications, organize them into groups based on topics and creating summaries, without significantly more. The claims recite additional elements or combination of elements, such as processor, and storage devices, but they do not amount to any more than mere instructions to implement the idea on a computer. The recitation of a generic computer structure serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry.
With respect to Step 2B, Examiner notes simply appending well-understood, routine,
conventional activities previously known to the industry, specified at a high level of generality,
to the judicial exception, is not indicative of an inventive concept (aka “significantly more”).
Storing and retrieving information such as stored sound samples in memory is well-understood,
routine, conventional computer functions as recognized by the court decisions listed in MPEP §
2106.05(d). The claim as a whole merely describes how to generally apply the concept of generating summaries of information in a computer environment.
Viewed as a whole, these additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. The additional dependent claims also do not yet contain limitations that transform the abstract idea into patent eligible subject matter. Examples of claims that recite mental processes include:
• a claim to “collecting information, analyzing it, and displaying certain results of the
collection and analysis,” where the data analysis steps are recited at a high level of generality
such that they could practically be performed in the human mind, Electric Power Group v.
Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);
• a claim to collecting and comparing known information (claim 1), which are steps that
can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen
IDEC, 659 F.3d 1057, 1067, 100 USPQ2d 1492, 1500 (Fed. Cir. 2011);
• See also example in Berkheimer v. HP, Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed.
Cir. 2018), in which the patentee claimed methods for parsing and evaluating data using a
computer processing system. The Federal Circuit determined that these claims were directed to
mental processes of parsing and comparing data, because the steps were recited at a high level of
generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125
USPQ2d at 1652-53.
Claims 2-7 are also rejected as they are also directed further toward generating summaries based on whether a user is busy or away, creating records of new topics, and tracking and updating topics significance using a computer system at a high level of generality.
Claims 8-20 are rejected for similar reasoning as provided above.
Claims 15-20 are also rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the computer program product in the claims is not limited to tangible computer-readable storage devices and may also be directed to a signal per se. See [0005] for Applicant’s disclosure, for example.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-5, 7-12, 14-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Leiba et al. (US 2018/0287981).
Claim 1
Leiba teaches a computer-implemented method for automatically and electronically generating a communication summary based on communications received on one or more electronic communication systems, comprising:
automatically determining whether new and different communications received on an electronic communication system relates to one or more stored topics of interest to the user (abstract, The present invention may include determining a plurality of message clusters from the plurality of missed messages, whereby a topic is associated with each message cluster. The present invention may include ranking the determined plurality of message clusters based on comparing the topic associated with each message cluster to the plurality of topics of interest. [0024], Topics of interest may be learned from the past interactions of the user derived from chat history or from a larger set of the user's social, collaboration, and business interactions.);
in response to determining that the received new and different communications relate to the one or more stored topics of interest, automatically extracting content from the new and different communications ([0027] The scored message rankings from the topics module and the social network module may be used to generate a single list that is re-ranked based on the combined score each message received from the topic module and the social network module. Thereafter the top N messages may be selected for generating a message summary for the user.), and associating and storing the extracted content associated with at least one new communication with at least one related topic of interest from the one or more stored topics of interest ([0038] After the missed messages 304 are collected over the time period the user was away, known algorithms may be used to cluster subsets of the missed messages 304 based on topic. [0038] The eight messages on the topic of camping may be clustered in a set of messages about camping and the 20 messages on the topic of football may be clustered in a set of messages about football.); and automatically generating and displaying the communication summary ([0044] After the top messages are picked at 312, the summary generation sub-system 302 presents the top messages as a summary of most relevant messages (i.e., top messages) that the user missed while away from the group chat or that were generated during a user-defined period of time. According to at least one embodiment, the summary message cluster topics may be presented to the user as round icons, or bubbles, whereby each message cluster topic may have a corresponding bubble.),
wherein the communication summary comprises the extracted content from the received new and different communications ([0043] Next, at 312, the message clusters are sorted and the top scored message clusters are picked for the summary. The message clusters in the missed messages 304 may be sorted based on the combined score determined previously at 310. According to at least one embodiment, the top N message clusters may be selected for generating a message summary for the user.), and
wherein displaying the communication summary further comprises presenting and labeling the new and different communications with the at least one related topic of interest ([0044], whereby each message cluster topic may have a corresponding bubble. ).
Claim 2
Leiba teaches the computer-implemented method of claim 1, wherein automatically determining whether the new and different communications received on the electronic communication system relates to the one or more stored topics of interest to the user further comprises:
automatically determining whether the new and different communications received on the electronic communication system relates to the one or more stored topics of interest to the user in response to detecting a first change to a user status on the electronic communication system ([0023], More specifically, group chat messages generated while a user is away or over a user-defined period of time may be analyzed and prioritized based on determining…messages that mention topics that the user is interested in),
wherein the new and different communications comprise communications received during a time period that the first change in the user status remains in effect ([0023], the messages may be sorted based on priority and a threshold number may be selected as a summary of relevant messages for the user to catch up on what transpired in group chat while the user was away).
Claim 3
Leiba teaches the computer-implemented method of claim 2, wherein the first change to the user status comprises a switch in the user status from an active status to an inactive status associated with a user and the electronic communication system ([0026] The summary generation sub-system may begin by receiving a set of group chat messages that were generated while the user was away as input.).
Claim 4
Leiba teaches the computer-implemented method of claim 1, wherein automatically generating and displaying the communication summary further comprises:
automatically generating and displaying the communication summary in response to detecting a second change to the user status, wherein detecting the second change to the user status comprises detecting a switch in the user status from an inactive status to an active status associated with a user and the electronic communication system ([0023], relevant messages for the user to catch up on what transpired in group chat while the user was away; [0037], A set of group chat messages that were generated while the user is away may be collected by determining the time when the user leaves the group chat and then comparing the time the user leaves to the time the returns to the group chat. [0076], A personalized chat summary program 110a, 110b provides a way to generate a personalized group chat summary of chat messages a user missed to present the most relevant missed messages to the user.).
Claim 5
Leiba teaches the computer-implemented method of claim 1, further comprising: tracking received communications on the one or more electronic communication systems; tracking user activity and interactions with the received communications (abstract: The present invention may include receiving a plurality of input interactions associated with the user.);
in response to detecting user interest in a communication based on the tracked user activity and interactions ([0024], Topics of interest may be learned from the past interactions of the user derived from chat history ), using natural language processing algorithms on the communication to identify and generate a topic of interest representative of the communication ([0025], The user-profile sub-system may include a processing and learning component that analyzes the input and extracts the user topics of interest and the user's social network. The user's social network may be a weighted list of people that are directly related to the user within a social media context. The output from the processing and learning component is a social network and the user's topics of interest. Topic extraction and social network analysis may be done, according to one embodiment, using a Latent Dirichlet Allocation (LDA) model for topic extraction).
Claim 7
Leiba teaches the computer-implemented method of claim 1, further comprising: ranking the one or more stored topics of interest; and automatically generating and displaying the new and different communications on the communication summary based on the ranking ([0043] Next, at 312, the message clusters are sorted and the top scored message clusters are picked for the summary.).
Claims 8-12, 14
These claims recite substantially the same limitations as those provided in claims 1-5, and 7 respectively and, therefore they are rejected for the same reasons.
Claims 15-19
These claims recite substantially the same limitations as those provided in claims 1-5 respectively, and therefore they are rejected for the same reasons.
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 6, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Leiba et al. (US 2018/0287981) in view of Chowdhury et al. (US 2016/0248716).
Claim 6
Leiba teaches the computer-implemented method of claim 5, further comprising: in response to determining that the generated topic of interest does not match the one or more stored topics of interest, generating a new entry on the database for the generated topic of interest ([0024], Topics of interest may be learned from the past interactions of the user derived from chat history [0033], Topics of interest 212 may be identified using an LDA model to analyze the input interactions 204 and then stored in a data repository, such as a database 114.). However Leiba does not explicitly detail assigning an interest percentage to the new entry; in response to determining that the generated topic of interest does match at least one stored topic of interest from the one or more stored topics of interest, updating the interest percentage for the at least one stored topic of interest matching the generated topic of interest.
Chowdhury teaches assigning an interest percentage to the new entry ([0037] The normalized interaction level can be stored in the message store along with the relevant message and any other information about the message (e.g., number of interactions, number of subscribers, types of interactions, identities of users interacting).);
in response to determining that the generated topic of interest does match at least one stored topic of interest from the one or more stored topics of interest, updating the interest percentage for the at least one stored topic of interest matching the generated topic of interest ([0060], As interaction information is received, the interaction information can be processed, and scores or rankings may be produced. This recent information may be used to update the recommendation status of the message (e.g., whether it should be highlighted). Updates can be performed repeatedly as new interaction data is received, and a score or rank for a particular message may fluctuate up and down over time. ).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to incorporate calculation of interest level as taught by Chowdhury with the summarization system of Leiba, because doing so would have enabled users to better focus their attention on messages that are likely to be interesting ([0016] of Chowdhury).
Claims 13 and 20
These claims recite substantially the same limitations as those provided in claims 6, and therefore they are rejected for the same reasons.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THOMAS H MAUNG whose telephone number is (571)270-5690. The examiner can normally be reached Monday-Friday, 9am-6pm, EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Carolyn R. Edwards can be reached at 1-(571) 2707136. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/THOMAS H MAUNG/Primary Examiner, Art Unit 2692