• A. Bhavani
• Dr.A.P.Siva Kumar

Novel semantic-based Social Q&A recommendation gadget for social networks, which suggests Social Q&A to users based on their lifestyle’s patterns rather than social graphs. By taking the benefit of sensor-rich smartphones, it discovers lifestyle’s types, of customers from consumer-centric sensor information, quantifies the resemblance of lifestyle’s patterns between users, and recommends Social Q&A to customers if their lifestyle’s patterns have excessive similarity. Inspired with the aid of text mining, extraction of a person’s day to day life as lifestyle’s documents, from that his /her lifestyle’s patterns is represented. Question and Answer (Q&A) structures play a necessary position in people’s life style for facts and ability sharing. Users place up queries and pick inquiries to reply at intervals for the convenience. Due to the hastily growing client in public and additionally the vary of queries, it’s not going for a user to return back upon a matter via hazard that (s ) he can answer. Also, unselfishness won’t encourage all users to produce answers, not to mention high satisfactory answers within a short time. The primary goal of this is to reinforce the general performance of Q&A systems by actively forwarding inquiries to customers who're successful and inclined to answer the queries. During this case, Social Q&A, a web social community-based Q&A machine is designed and applied. The social community homes of commonplace-hobby associated mutual-agree with friend entreaty to understand an asker via friendship who are maximumly probable to reply the question and enhance the client protection is influenced by Social Q&A. A tendency, in addition, to improving Social Q&A with security and efficiency enhancements via defensive client privacy and identifies and retrieving answers automatically for repeated queries. Another tendency is that the structure and algorithms are described and a comprehensive massive-scale simulation to judge Social Q&A in distinction with totally different ways is applied. The effects propose that social networks are also influenced to boost the solution exceptional and asker’s ready time.

Interest Analyzer, Question-User Mapper, Interest similarity, Friends Count.

"An Online Social Network Based Q&A System With Large User Base", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.210-214, July-2018, Available :http://www.jetir.org/papers/JETIR1807380.pdf

"An Online Social Network Based Q&A System With Large User Base", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp210-214, July-2018, Available at : http://www.jetir.org/papers/JETIR1807380.pdf