Abstract
This paper presents a topic discovery approach based on multi-ant colonies clustering combination. The algorithm consists of three parts. First, each document is represented as a vector of features in a vector space model. Then a hypergraph model is used to combine the clusterings produced by three kinds of ant-based algorithms with different moving speed. Finally, the topic of each cluster is extracted by re-computing the term weights. Test results show that the number of topics can be adaptively determined and clustering combination can improve the system performance.
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Yang, Y., Kamel, M., Jin, F. (2005). Topic Discovery from Document Using Ant-Based Clustering Combination. In: Zhang, Y., Tanaka, K., Yu, J.X., Wang, S., Li, M. (eds) Web Technologies Research and Development - APWeb 2005. APWeb 2005. Lecture Notes in Computer Science, vol 3399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31849-1_11
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DOI: https://doi.org/10.1007/978-3-540-31849-1_11
Publisher Name: Springer, Berlin, Heidelberg
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