PATENT CLAIM ANALYSIS

Application Number: 15901040
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-06
Patent Classification: ["706", "052000"]

Abstract:
The present invention provides a computer implemented method, a system, and a computer program product of identifying and analyzing the impact of an event associated with an entity on relationships of the entity. In an exemplary embodiment, the present invention includes storing data that identifies relationships with entities associated with the entity, based on data about the entity and data about the entities from at least one online website, storing data that identifies entity relationships, among the entity relationships identified in an entity relationship data structure, that are determined by the computer system to be affected by events associated with event categories, receiving data about events related to the entity, and outputting data related to a recommendation for a second entity among the entities associated with the entity, wherein the second entity corresponds to a most affected relationship, based on data associated with the second entity.

Claim (Index 1):
A computer implemented method comprising:\n storing, by a computer system, data that identifies relationships with entities associated with an entity (entity relationships), based on data about the entity and data about the entities from at least one online website, in a first data structure (entity relationship data structure),\n wherein the storing data that identifies relationships with the entities associated with the entity comprises analyzing, by the computer system, at least one of at least one online social media profile of the entity, at least one online social media feed of the entity, at least one online presence of the entity, at least one online blog of the entity, at least one online career profile of the entity, at least one online description of at least one hobby of the entity, and at least one online description of at least one activity of the entity; \n storing, by the computer system, data that identifies entity relationships, among the entity relationships identified in the entity relationship data structure, that are determined by the computer system to be affected by events associated with event categories, in a second data structure (impact data structure); receiving, by the computer system, data about events related to the entity (entity events), wherein the data comprises types of the entity events (event types),\n wherein the receiving comprises obtaining, by the computer system, data from at least one online social media post of the entity; \n identifying, by the computer system, based on a parsing by the computer system of the received data, impacting events among the entity events, wherein the impacting events are determined by the computer system to impact the entity relationships identified in the impact data structure,\n wherein the identifying from the received data the impacting events comprises classifying, by the computer system, at least one social media post of the entity as an impacting event among the impacting events based on at least an analysis by the computer system of at least one text string identified by the computer system in the post; \n for each impacting event among the impacting events, calculating, by the computer system, an impact score based on at least the event categories, data about sentiment about the impacting event, and an event type of the impacting event, thereby resulting in calculated impact scores; for each impacting event among the impacting events, identifying, by the computer system, likely affected relationships (LARs) among the entity relationships identified in the impact data structure based on the calculated impact scores,\n wherein the identifying LARs comprises using, by the computer system, at least one of heuristics, accumulated data describing interactions between the entity and the entities associated with the entity, and calculated relationship weightings; \n for each likely affected relationship (LAR) among the LARs for each impacting event among the impacting events, calculating, by the computer system, at least an emotional index value and a relation index value,\n wherein the calculating at least the emotional index value and the relation index value comprises identifying, by the computer system, commonalities between the entity and the LAR; \n for each LAR among the LARs for each impacting event among the impacting events, calculating a final reaction score value based on at least a previous reaction score value for the LAR, the relation index value for the LAR, and the event type of the impacting event, thereby resulting in final reaction scores for the LARs; identifying, by the computer system, a most affected relationship (MAR) among the LARs for each impacting event among the impacting events based on the final reaction scores; and outputting, by the computer system, data related to a recommendation for a second entity among the entities associated with the entity, wherein the second entity corresponds to the MAR, based on data associated with the second entity (second entity data),\n wherein the outputting comprises executing, by the computer system, an algorithm that performs a psychographic profile analysis of the second entity based on the second entity data.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 88.0
- Lexical Diversity: 2.44615
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14573729', '15717509', '10924702', '14932336', '12709823']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3166963080371213
- 35 USC 102 Novelty (BERT): 0.4899350540005945
- Combined Prediction Score: 0.3340201826334686
- Mean Citation Score: 158.001872
- Max Citation Score: 161.07246
- Similarity Product: 103.82222480043411

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

Dataset: test