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Social Analytics driven predictive text assist Disclosure Number: IPCOM000247793D
Publication Date: 2016-Oct-06
Document File: 3 page(s) / 135K

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The Prior Art Database


On a cross platform messaging system include an additional / secondary dictionary which source data from trending topics from various social channels. This dictionary would assist the end users in messaging on being able to type accurately on trending topics and could be configured to be location or region specific.

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Social Analytics driven predictive text assist

Dictionaries embedded into Smart Phones ease the messaging by allowing use of words through auto  completion instead of typing the whole word. However, sometimes typing the words takes much more  time as than intended as the dictionary is not helpful in most cases. 

In the social world we live in today a good part of the conversations are around the trending topics.  Example, post the India‐Bangladesh T20 World Cup 2016 match, most of us were trying to write  "Pandya's WWW .... " or "Did you watch ...". In such a scenario Hardik Pandya was not yet in our  messaging dictionaries and typing it for the first time was too time consuming and confusing.

There is a definite need for a newer typing assist. What we have thought of is a second parallel  dictionary called the "Social Trending dictionary".

This article includes a "Social Trending dictionary" which would show up in parallel with the existing  dictionary while using messaging apps on Smart phones. This would be a new dynamic dictionary which  is updated based on trending data on reputed social networking sites around the World and is location  specific as well.

‐ Location specific would mean, when someone types "Are you watching" it would bring up IPL (Cricket...