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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jianxiong Yang Watada, J. |
| Copyright Year | 2011 |
| Description | Author affiliation: Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan (Jianxiong Yang; Watada, J.) |
| Abstract | Latent Semantic Indexing (LSI) is an information retrieval technique using a low-rank singular value decomposition (SVD) of term-document matrix. The aim of this method is to reduce the matrix dimension by finding a pattern in document collection with concurrently referring terms. The methods are implemented to calculate the weight of term-document in vector space model (VSM) for document clustering using fuzzy clustering algorithm. LSI is an attempt to exploit the underlying semantic structure of word usage in documents. During the query-matching phase of LSI, a user's query is first projected into the term-document space, and then compared to all terms and documents represented in the vector space. Using some similarity measure, the nearest (most relevant) terms and documents are identified and returned to the user. The current LSI query-matching method requires computing the similarity measure about the query of every term and document in the vector space. In this paper, the Maximal Tree Algorithm is used within a recent LSI implementation to mitigate the computational time and computational complexity of query matching. The Maximal Tree data structure stores the term and document vectors in such a way that only those terms and documents are most likely qualified as the nearest neighbor to the query will be examined and retrieved. In a word, this novel algorithm is suitable for improving the accuracy of data miners. |
| Starting Page | 976 |
| Ending Page | 983 |
| File Size | 238721 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424473151 |
| ISSN | 10987584 |
| e-ISBN | 9781424473175 |
| e-ISBN | 9781424473168 |
| DOI | 10.1109/FUZZY.2011.6007525 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-06-27 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Large scale integration Matrix decomposition Semantics Accidents Indexing Economics Singular value decomposition SVD Fuzzy clustering data mining LSI |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Theoretical Computer Science Software |
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