Supervised topic models with word order structure for document classification and retrieval learning-Reference-Cited by-同舟云学术

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Supervised topic models with word order structure for document classification and retrieval learning

Published:2015-06-04 Issue:4 Volume:18 Page:283-330
ISSN:1386-4564
Container-title:Information Retrieval Journal
language:en
Short-container-title:Inf Retrieval J

Author:

Jameel Shoaib,Lam Wai,Bing Lidong

Funder

Research Grant Council of the Hong Kong Special Administrative Region, Direct Grant of the Faculty of Engineering, CUHK

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Information Systems

Link

http://link.springer.com/content/pdf/10.1007/s10791-015-9254-2.pdf

Reference122 articles.

1. Acharya, A., Rawal, A., Mooney, R. J., & Hruschka, E. R. (2013). Using both latent and supervised shared topics for multitask learning. In Machine Learning and Knowledge Discovery in Databases, pp. 369–384.

2. Aldous, D. (1985). Exchangeability and related topics. École d’Été de Probabilités de Saint-Flour XIII-1983, 1117, 1–198.

3. Allan, J. (2005). HARD track overview in TREC 2003 high accuracy retrieval from Documents. Technical report, DTIC Document.

4. Andrzejewski, D., & Buttler, D. (2011). Latent topic feedback for Information Retrieval. In Knowledge Discovery and Data Mining, pp. 600–608.

5. Asadi, N., & Lin, J. (2013). Effectiveness/efficiency tradeoffs for candidate generation in multi-stage retrieval architectures. In Special Interest Group on Information Retrieval, pp. 997–1000.

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