Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Mining Ontological Knowledge from Domain-Specific Text Documents
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
A simple but powerful automatic term extraction method
COMPUTERM '02 COLING-02 on COMPUTERM 2002: second international workshop on computational terminology - Volume 14
Automatic Chinese Multi-word Term Extraction
ALPIT '08 Proceedings of the 2008 International Conference on Advanced Language Processing and Web Information Technology
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The number of online software services based on SaaS paradigm is increasing. However, users usually find it hard to get the exact software services they need. At present, tags are widely used to annotate specific software services and also to facilitate the searching of them. Currently these tags are arbitrary and ambiguous since mostly of them are generated manually by service developers. This paper proposes a method for mining tags from the help documents of software services. By extracting terms from the help documents and calculating the similarity between the terms, we construct a software similarity network where nodes represent software services, edges denote the similarity relationship between software services, and the weights of the edges are the similarity degrees. The hierarchical clustering algorithm is used for community detection in this software similarity network. At the final stage, tags are mined for each of the communities and stored as ontology.