Paper
20 June 2014 TrustQ: a category reputation based question and answer system
Yuhua Lin, Haiying Shen
Author Affiliations +
Abstract
Question and Answering (Q/A) systems aggregate the collected intelligence of all users to provide satisfying answers for questions. A well-developed Q/A system should provide high question response rate, low response delay and good answer quality. Previous works use reputation systems to achieve the goals. However, these reputation systems evaluate a user with an overall rating for all questions the user has answered regardless of the question categories, thus the reputation score cannot accurately reflect the user's ability to answer a question in a specific category. In this paper, we propose TtustQ, a category reputation based Q/A System. TtustQ evaluates users' willingness and capability to answer questions in different categories. Considering a user has different willingness to answer questions from different users, TtustQ lets each node evaluate the reputation of other nodes answering its own questions. User a calculates user b's final reputation by considering both user a's direct rating and the indirect ratings on user b from other nodes. The reputation values facilitate forwarding a question to potential answerers, which improves the question response rate, response delay and answer quality. Our trace-driven simulation on PeerSim demonstrates the effectiveness of TtustQ in providing good user experience in terms of response rate and latency, and the answer quality.
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Yuhua Lin and Haiying Shen "TrustQ: a category reputation based question and answer system", Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 90911N (20 June 2014); https://doi.org/10.1117/12.2050610
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KEYWORDS
Fluctuations and noise

Systems modeling

Computing systems

Mathematical modeling

Receivers

Quality systems

Social networks

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