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Lot of information is shared by the user through various social media posts, blogs and opinions. With so much information being shared, how can this unstructured information be leveraged to tailor useful information to the user. If you start start analyzing, you would come across a variety of applications which are currently untapped. I am presenting one such application called “Social MATCH MAKING”.

Social Match Making is a term I coined to use insights from a user activity (blogs, tweets, usually various matrimonial/finder websites employ about yourself details) to understand the social and physiological aspects and use this to compare traits from other prospects/users. For example, in Indian tradition, usually a “kundli” or astrology birth chart is compared to see if a match is compatible using various scientific calculations and planetary positions. Similarly you could use Insights to compare traits and arrive at a conclusion.

Give it a try, use the Watson Personality Insights and compare traits from users to find like minded or persons from opposite kind from your social media groups. You can easily build an application, that sources profiles from social media groups or geo-locations to analyse and compare profiles based on social and cognitive characteristics. Not only social mediums, this concept can be used within a community, intranet or an enterprise or to to drive events (movies, restaurants, places of interest any more) matching a user interest.

I liked the concept of Watson Personality Insights, but I feel in the current form its provides limited capability, particularly requiring a 2000 words to arrive at proper analytics. Getting those 2000 words is a challenge and the implementation could have been way better.

 

Tags : cognitivecognitive computingcognitive-computing-featured
Naveen

The author Naveen