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Author:

Dani, Harsh (Dani, Harsh.) | Morstatter, Fred (Morstatter, Fred.) | Hu, Xia (Hu, Xia.) | Yang, Zhen (Yang, Zhen.) (Scholars:杨震) | Liu, Huan (Liu, Huan.)

Indexed by:

CPCI-S Scopus

Abstract:

Social networking or social media sites are involved in our daily life. With the increasing popularity of social media sites like Twitter and Facebook, people are using their social network to find answers to their questions. Not every social media site can answer a user's question. Different social media sites have different strength such as the StackOverflow community has specific interest in programming and software development, whereas the TripAdvisor community has specific interest in topic of Travel. Hence, we need a framework to identify social media sites, which can best answer user's questions. In this paper, we demonstrate system named Social Answer which can rank social media sites for user's query based on the content similarity of social media site and user's query using ensemble of search engine query results.

Keyword:

Q&A Conflict Allocation Social Media

Author Community:

  • [ 1 ] [Dani, Harsh]Arizona State Univ, Comp Sci & Engn, Tempe, AZ 85281 USA
  • [ 2 ] [Morstatter, Fred]Arizona State Univ, Comp Sci & Engn, Tempe, AZ 85281 USA
  • [ 3 ] [Liu, Huan]Arizona State Univ, Comp Sci & Engn, Tempe, AZ 85281 USA
  • [ 4 ] [Yang, Zhen]Texas A&M Univ, Comp Sci & Engn, College Stn, TX 77843 USA
  • [ 5 ] [Hu, Xia]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China

Reprint Author's Address:

  • [Dani, Harsh]Arizona State Univ, Comp Sci & Engn, Tempe, AZ 85281 USA

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Source :

2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW)

Year: 2015

Page: 1632-1635

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

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