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Reseach Article

Mining Consumption Intent from Social Data: A Survey

Published on September 2016 by Faizan Khan, Samarjeet Borah, Ashis Pradhan
International Conference on Computing and Communication
Foundation of Computer Science USA
ICCC2016 - Number 1
September 2016
Authors: Faizan Khan, Samarjeet Borah, Ashis Pradhan
bae2d3a9-7472-458c-a2e0-86a4532c5683

Faizan Khan, Samarjeet Borah, Ashis Pradhan . Mining Consumption Intent from Social Data: A Survey. International Conference on Computing and Communication. ICCC2016, 1 (September 2016), 14-20.

@article{
author = { Faizan Khan, Samarjeet Borah, Ashis Pradhan },
title = { Mining Consumption Intent from Social Data: A Survey },
journal = { International Conference on Computing and Communication },
issue_date = { September 2016 },
volume = { ICCC2016 },
number = { 1 },
month = { September },
year = { 2016 },
issn = 0975-8887,
pages = { 14-20 },
numpages = 7,
url = { /proceedings/iccc2016/number1/26153-cc54/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Computing and Communication
%A Faizan Khan
%A Samarjeet Borah
%A Ashis Pradhan
%T Mining Consumption Intent from Social Data: A Survey
%J International Conference on Computing and Communication
%@ 0975-8887
%V ICCC2016
%N 1
%P 14-20
%D 2016
%I International Journal of Computer Applications
Abstract

Social Media is a rich source of information about the desires and needs of users to buy a product or service. There lies a huge opportunity in mining the Intent of users which can be applicable to the field of marketing, ecommerce, recommender systems, etc. This survey focuses on analyzing the techniques that can be used to mine the Intent of users from social data. Notable works that have contributed towards determining the Intent of users from social data has been highlighted.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Consumption Intent Intent Mining Feature Extraction Text Classification Machine Learning.