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System for Tracking Historical Change in Psycholinguistic Profile Recommendation Services

IP.com Disclosure Number: IPCOM000246017D
Publication Date: 2016-Apr-26
Document File: 3 page(s) / 46K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system that clusters a user’s social network content contributions over a timeline, creates a pscholinguistic profile for each cluster of content, and then performs an analysis to determine changes in the user’s psycholinguistic profile attributes for each cluster over the timeline. Identified changes indicate a change in mental state or mode of thought regarding a product or service, which is then used to generate notifications to interested third parties or provide recommendations for goods and services to the user.

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System for Tracking Historical Change in Psycholinguistic Profile Recommendation Services

Understanding a person's personality traits over a given period can help identify changes in behavior, thinking, or brand preferences. For example, a mobile device manufacturer can use the knowledge of a consumer's personality trends to understand that the user no longer prefers a product, enabling the company to be proactive about the change in mentality; at the same time, the newly preferred manufacturer can receive notification about a potential new customer.

Applying the concepts of psycholinguistics to a user on social media and other data sources over a given period allows analysts to recognize a change or trend in the user's thinking, behavior, and preferences.

One existing solution provides an enhanced recommendation engine that can drive product and service sales using psycholinguistic profiles and the location of geo-clustered users in social media; however, it does not provide a method for tracking the clusters over a given period.

A method and system are needed to track changes in a user's psycholinguistic profile trends based on historical data analysis, and accordingly recommend appropriate goods and services to the user.

Disclosed is a system that clusters a user's social network content contributions over a given timeline (e.g., weekly, monthly, quarterly, etc.) and then creates a pscholinguistic profile for each cluster of social content. The cluster durations are generated automatically based on volume sufficient to create a complete psycholinguistic profile, or statically defined.

The system then analyzes the clusters to determine changes in the user's psycholinguistic profile attributes for each cluster in the timeline. The identified changes or trends in the psycholinguistic profile over a period are validated against a knowledge base (i.e. profile attributes) to determine whether the change(s) indicate a correlation with a change in mental state or preferences. The resulting data is ultimately used to create and provide notifications to interested parties of the changes and/or provide the user with targeted recommendations of goods and services.

The change or trend analysis of the user's psycholinguistics profile can be used for wide range of applications. The analysis can be applied to predict a user's medical conditions, understand that a customer no longer prefers a product or brand, or identify that a new potential customer exists for a product or brand. In addition, based on the user's changes of choice, the system can recommend appropriate products and services or target advertising.

The components of the novel system and method include:


 Social network software

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 User content contribution over timeline used to define psycholinguistic profile


 Cognitive system


 Recommendations Engine


 Notification system using various channels (e.g., email, instant message, text, etc.)

Invention Implem...