Please use this identifier to cite or link to this item: https://doi.org/10.1145/1645953.1646071
Title: Exploiting internal and external semantics for the clustering of short texts using world knowledge
Authors: Hu, X.
Sun, N. 
Zhang, C.
Chua, T.-S. 
Keywords: Clustering
Semantic knowledge bases
Short texts
Syntactic structure
Issue Date: 2009
Source: Hu, X.,Sun, N.,Zhang, C.,Chua, T.-S. (2009). Exploiting internal and external semantics for the clustering of short texts using world knowledge. International Conference on Information and Knowledge Management, Proceedings : 919-928. ScholarBank@NUS Repository. https://doi.org/10.1145/1645953.1646071
Abstract: Clustering of short texts, such as snippets, presents great challenges in existing aggregated search techniques due to the problem of data sparseness and the complex semantics of natural language. As short texts do not provide sufficient term occurring information, traditional text representation methods, such as ''bag of words" model, have several limitations when directly applied to short texts tasks. In this paper, we propose a novel framework to improve the performance of short texts clustering by exploiting the internal semantics from original text and external concepts from world knowledge. The proposed method employs a hierarchical three-level structure to tackle the data sparsity problem of original short texts and reconstruct the corresponding feature space with the integration of multiple semantic knowledge bases - Wikipedia and WordNet. Empirical evaluation with Reuters and real web dataset demonstrates that our approach is able to achieve significant improvement as compared to the state-of-the-art methods. Copyright 2009 ACM.
Source Title: International Conference on Information and Knowledge Management, Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/42135
ISBN: 9781605585123
DOI: 10.1145/1645953.1646071
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