All Outputs (5)

Relation discovery from web data for competency management. (2007)
Journal Article
ZHU, J., GONCALVES, A.L., UREN, V.S., MOTTA, E., PACHECO, R., EISENSTADT, M. and SONG, D. 2007. Relation discovery from web data for competency management. Web intelligence and agent systems [online], 5(4), pages 405-417. Available from: https://content.iospress.com/articles/web-intelligence-and-agent-systems-an-international-journal/wia00124

In current organizations, valuable enterprise knowledge is often buried under rapidly expanding huge amount of unstructured information in the form of web pages, blogs, and other forms of human text communications. We present a novel unsupervised mac... Read More about Relation discovery from web data for competency management..

Learning and optimization of an aspect hidden markov model for query language model generation. (2007)
Conference Proceeding
HUANG, Q., SONG, D., RUGER, S. and BRUZA, P. 2007. Learning and optimization of an aspect hidden markov model for query language model generation. In Dominich, S. and Kiss, F. (eds.) Studies in theory of information retrieval: proceedings of the 1st Association of Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR) international conference on the theory of information retrieval (ICTIR'07), 18-20 October 2007, Budapest, Hungary. Budapest: Foundation for Information Society (INFOTA), pages 157-164.

The Relevance Model (RM) incorporates pseudo relevance feedback to derive query language model and has shown a good performance. Generally, it is based on uni-gram models of individual feedback documents from which query terms are sampled independent... Read More about Learning and optimization of an aspect hidden markov model for query language model generation..

An intelligent information agent for document title classification and filtering in document-intensive domains. (2007)
Journal Article
SONG, D., LAU, R.Y.K., BRUZA, P.D., WONG, K.-F. and CHEN, D.-Y. 2007. An intelligent information agent for document title classification and filtering in document-intensive domains. Decision support systems [online], 44(1), pages 251-265. Available from: https://doi.org/10.1016/j.dss.2007.04.001

Effective decision making is based on accurate and timely information. However, human decision makers are often overwhelmed by the huge amount of electronic data these days. The main contribution of this paper is the development of effective informat... Read More about An intelligent information agent for document title classification and filtering in document-intensive domains..

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 induction via fuzzy C-means clustering in a high dimensional semantic space. (2007)
Book Chapter
SONG, D., CAO, G., BRUZA, P.D. and LAU, R.Y.K. 2007. Concept induction via fuzzy C-means clustering in a high dimensional semantic space. In Valente de Oliveira, J. and Pedrycz, W. (eds.) Advances in fuzzy clustering and its applications. Chichester: Wiley [online], chapter 19, pages 393-403. Available from: https://www.wiley.com/en-gb/Advances+in+Fuzzy+Clustering+and+its+Applications-p-9780470061183

Lexical semantic space models have recently been investigated to automatically derive the meaning (semantics) of information based on natural language usage. In a semantic space, a term can be considered as a concept represented geometrically as a ve... Read More about Concept induction via fuzzy C-means clustering in a high dimensional semantic space..