PATENT CLAIM ANALYSIS

Application Number: 16019453
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-10
Patent Classification: ["707", "734000"]

Abstract:
Embodiments of the present invention provide methods, systems, apparatuses, and computer program products for integrating user-specific context indicators into a searchable enterprise platform. In one embodiment, an apparatus is configured to apply a learned user profile, to a set of search results to obtain a user-specific, ranked arrangement of search results. The learned user profile may be developed through the application of a machine learning and/or trained model to a set of user behaviors that have been determined or otherwise detected within an enterprise platform, such that the user-specific context in which a user's search arises can be modeled and applied to retrieved digital content items associated with a search query within the enterprise platform.

Claim (Index 12):
The computer program product of  claim 11 , wherein applying the set of search results and the set of learned user profile values associated with the user profile to the multiple additive regression trees model to produce the user-specific digital content item set comprises:\n applying a plurality of profile context weights to each digital content item of the set of search results, wherein the profile context weights are based at least in part on the set of learned user profile values; ranking each digital content item of the set of search results according to the applied profile context weights; and arranging the set of search results according to the ranking.

Metadata:
- Claim Count in Document: 35.0
- Percentile: 94.0
- Lexical Diversity: 1.61538
- Patent Class: 707.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15633640', '15633598', '11770027', '15156399', '12873622']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2318642047377154
- 35 USC 102 Novelty (BERT): 0.5294277292285464
- Combined Prediction Score: 0.2616205571867985
- Mean Citation Score: 227.500872
- Max Citation Score: 366.5972
- Similarity Product: 269.8832556507587

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 0

Dataset: test