With the advent and growth of online bookstores, the importance of book reviews has been increased due to the difficulty to browse actual contents of books in advance. This has led to the necessity of adequate systems for retrieving useful book reviews. Recently, ranking algorithms have been proposed for this purpose. However, most of them cannot consider discussions among users through replies. User discussion is an essential factor in ranking book reviews since it provides additional information. Although a state-of-theart algorithm with consideration of the factor has been proposed, it deals with the discussions only in view of reviewers’ participation. In this paper, we propose a ranking algorithm of estimating discussion quality on the basis of all the users engaging in discussions. Experimental results show that our algorithm outperforms the state-of-the-art one in terms of precision, recall, and NDCG.
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- Ranking Method for Book Reviews Based on Estimated Discussion Quality
- Springer Berlin Heidelberg