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A Hidden Topic-Based Framework toward Building Applications with Short Web Documents

Phan, Xuan Hieu and Nguyen, Cam Tu and Le, Dieu Thu and Nguyen, Le Minh and Horiguchi, Susumu and Ha, Quang Thuy (2011) A Hidden Topic-Based Framework toward Building Applications with Short Web Documents. IEEE Transactions on Knowledge and Data Engineering, 23 (7). pp. 961-976. ISSN 1041-4347

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This paper introduces a hidden topic-based framework for processing short and sparse documents (e.g., search result snippets, product descriptions, book/movie summaries, and advertising messages) on the Web. The framework focuses on solving two main challenges posed by these kinds of documents: 1) data sparseness and 2) synonyms/homonyms. The former leads to the lack of shared words and contexts among documents while the latter are big linguistic obstacles in natural language processing (NLP) and information retrieval (IR). The underlying idea of the framework is that common hidden topics discovered from large external data sets (universal data sets), when included, can make short documents less sparse and more topic-oriented. Furthermore, hidden topics from universal data sets help handle unseen data better. The proposed framework can also be applied for different natural languages and data domains. We carefully evaluated the framework by carrying out two experiments for two important online applications (Web search result classification and matching/ranking for contextual advertising) with large-scale universal data sets and we achieved significant results.

Item Type: Article
Subjects: Information Technology (IT)
ISI-indexed journals
Divisions: Faculty of Information Technology (FIT)
Depositing User: A/Prof. Xuan Hieu Phan
Date Deposited: 14 Nov 2016 02:37
Last Modified: 14 Nov 2016 02:37

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