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Title:Categorization of musicology questions from community-based Q&A site using latent dirichlet allocation
Author(s):Fu, Hengyi
Subject(s):Music information retrieval
Document representation
Topic models
Latent dirichlet allocation
Social Q&A site
Abstract:Question & Answer websites, such as Yahoo! Answer and Stack Exchange, are widely used to look for and exchange information in different knowledge domains. Question-answer pairs extracted from social Q&A sites can be considered as query and returned results in an information retrieval system, and descriptive access points are the intermediary to connect the information needs and information. However, information seekers sometimes experienced difficulty in precisely describing access points, and relied on system-suggested access points to search information. This study is the first attempt to perform automatic topic modeling (Latent Dirichlet Allocation) based on the text of questions and answers related to a wide range of musical topics. The analyses confirm that LDA is a very effective tool to classify textual, unstructured, music-related data and the identified topics and question types are similar to expert cataloging based on the same set of data.
Issue Date:2017
Citation Info:Fu, H. (2017). Categorization of Musicology Questions from Community-based Q&A Site Using Latent Dirichlet Allocation. In iConference 2017 Proceedings (pp. 317-324).
Series/Report:iConference 2017 Proceedings
Genre:Conference Paper / Presentation
Rights Information:Copyright 2017 Hengyi Fu
Date Available in IDEALS:2017-07-27

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