Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/7620
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDeb, S.-
dc.contributor.authorMohan, S.-
dc.contributor.authorVenkatraman, P.-
dc.contributor.authorBindu, P.V.-
dc.contributor.authorSanthi Thilagam, P.-
dc.date.accessioned2020-03-30T10:02:33Z-
dc.date.available2020-03-30T10:02:33Z-
dc.date.issued2016-
dc.identifier.citationInternational Conference on Electrical, Electronics, and Optimization Techniques, ICEEOT 2016, 2016, Vol., , pp.4915-4920en_US
dc.identifier.urihttps://idr.nitk.ac.in/jspui/handle/123456789/7620-
dc.description.abstractShort message strings are widely prevalent in the age of social networking. Taking Facebook as an example, a user may have many other users in his contact list. However, at any given time frame, the user interacts with only a small subset of these users. In this paper, we propose a recommender system that determines which users have common interests based on the content of the short message strings of different users. The system calculates the similarity between two users based on the contents of short message strings by the users over a certain time period. A similarity measure based on short message strings must be temporal study as the contents of the short messages vary rapidly over time. Experimental study is conducted in the Facebook domain using status updates of users. � 2016 IEEE.en_US
dc.titleDeriving temporal trends in user preferences through short message stringsen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.