DETAILED ACTION
1. This action is responsive to Application no.18/602,006 filed 3/11/2024. All claims have been examined and are currently pending.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
3. The information disclosure statement (IDS) submitted 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 § 102
4. 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 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.
5. 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
6. Claim(s) 1-2 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ross et al (11,599,728).
Regarding claim 1 Ross et al (11,599,728) teaches A system for implementing a content-intelligence platform (abstract: apparatus, methods, systems and computer program products;
fig 1A,1B, 7;
col 1 l. 30-33: The Topic Engine reduces the processing burden by leveraging captured sequences of accessed content according to content identifiers in order to generate clusters of semantically related content identifiers;
col 4 l. 10-30), comprising:
a first data storage device storing a corpus of data for an enterprise (fig 1A,1B, 7;
col 3 l. 18-24: A diagram of exemplary network environment in which embodiments may operate is shown in FIG. 1A. In the exemplary environment 140, two clients 141, 142 are connected over a network 145 to a server 150 having local storage 151. Clients and servers in this environment may be computers. Server 150 may be configured to handle requests from clients;
col 4 l. 31-41 content corpus; l. 42-49 user accounts of the publishing platform);
a processing device that is configured (fig 1A,1B, 7; col 4 l. 10-30) to:
perform a text vectorization on the corpus of data (col 5 l.55-59: vector representation of each content identifier);
cluster text vectors for the corpus of data (col 6 l.22-24: feeds the reduced vector representations returned by the dimensionality reduction model into a clustering model);
extract topics from the clustered text vectors (col 6 l. 20-21: The Topic Engine generates clusters of semantically related content identifiers with direct access of the referenced content; l. 29-41; col 8 l. 1: second set of clusters; l. 20-25 granular subclusters);
cluster the extracted topics according to a similarity (col 5 l. 32-35 generate clusters of semantically related content identifiers);
store clusters of the extracted topics in a second data storage device (fig 1A,1B, 7; col 3 l. 18-32; col 4 l. 10-30);
parse text from the corpus of data (col 7 l. 9-10 extracts keywords and/or phrases from content);
calculate key words and key phrases (col 7 l. 9-10 extracts keywords and/or phrases from content);
perform a vectorization of the key words and key phrases (col 7 l. 17-21 feed the extracted keywords in an embedding model);
apply a similarity ranking to the vectorization of the key words and key phrases (col 7 l. 40-41: The Topic Engine generates a ranked list of the obtained set of words)
store results of the similarity ranking in the second data storage device (fig 1A,1B, 7; col 3 l. 18-32; col 4 l. 10-30); and
output selected topics, key words and key phrases as content intelligence for content delivery for the enterprise (col 7 l. 46-47: topic model returns a topic for each submitted ranked list).
Claim 2 recites limitations similar to claim 1 and is rejected for similar rationale and reasoning
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: See PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAUN A ROBERTS whose telephone number is (571)270-7541. The examiner can normally be reached Monday-Friday 9-5 EST.
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/SHAUN ROBERTS/Primary Examiner, Art Unit 2655