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A latent variable model for query expansion using the Hidden Markov Model (2008)
Presentation / Conference
HUANG, Q. and SONG, D. 2008. A latent variable model for query expansion using the Hidden Markov model. In Proceedings of the 17th Association for Computing Machinery (ACM) international conference on information and knowledge management (CIKM'08), 26-30 October 2008, Napa Valley, USA. New York: ACM [online], pages 1417-1418. Available from: https://doi.org/10.1145/1458082.1458310

We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed LVM, the combinations of query terms are viewed as the latent variable... Read More about A latent variable model for query expansion using the Hidden Markov Model.

Dimensionality reduction for dimension-specific search. (2007)
Presentation / Conference
HUANG, Z., SHEN, H., ZHOU, X., SONG, D. and RUGER, S. 2007. Dimensionality reduction for dimension-specific search. In Proceedings of the 30th Annual international Association of Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR) conference on research and development in information retrieval (SIGIR'07), 23-27 July 2007, Amsterdam, Netherlands. New York: ACM [online], pages 849-850. Available from: https://doi.org/10.1145/1277741.1277940

Dimensionality reduction plays an important role in efficient similarity search, which is often based on k-nearest neighbor (k-NN) queries over a high-dimensional feature space. In this paper, we introduce a novel type of k-NN query, namely condition... Read More about Dimensionality reduction for dimension-specific search..

Concept learning and information inferencing on a high-dimensional semantic space. (2004)
Presentation / Conference
SONG, D., BRUZA, P. and COLE, R. 2004. Concept learning and information inferencing on a high-dimensional semantic space. Presented at the 2004 Association of Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR) workshop on mathematical/formal methods in information retrieval (MF/IR 2004), 25-29 July 2004, Sheffield, UK.

How to automatically capture a significant portion of relevant background knowledge and keep it up-to-date has been a challenging problem encountered in current research on logic based information retrieval. This paper addresses this problem by inves... Read More about Concept learning and information inferencing on a high-dimensional semantic space..

A comparison of various approaches for using probabilistic dependencies in language modeling. (2003)
Presentation / Conference
BRUZA, P. and SONG, D. 2003. A comparison of various approaches for using probabilistic dependencies in language modeling. In Proceedings of the 26th Annual international Association of Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR) conference on research and development in information retrieval (SIGIR'03), 28 July - 1 August 2003, Toronto, Canada. New York: ACM [online], pages 419-420. Available from: https://doi.org/10.1145/860435.860530

The goals of this article is to study several estimates of relevance models which will be computed based on differing approaches for incorporating term dependency information. In this way, we hope to shed light on the relative merits of term dependen... Read More about A comparison of various approaches for using probabilistic dependencies in language modeling..