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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Thongkrau, T. Lalitrojwong, P. |
| Copyright Year | 2010 |
| Description | Author affiliation: Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand (Thongkrau, T.; Lalitrojwong, P.) |
| Abstract | A lexical ontology is useful as the basic knowledge base in artificial intelligence and computational linguistics application. However, it is insufficient to recognize only existing instances for each concept. Adding new instances into the lexical ontology will expand knowledge in the system. In this paper, we propose an efficient unsupervised instance population system that classifies new instances into a corresponding lexical ontology concept. Compared to previous related works, it does not require manual preprocessing to prepare training data. In terms of processing time, it does not need to search for many concepts in the lexical ontology. Furthermore, it is able to handle an unlimited number of ontological concepts in any domain. Our system employs latent semantic analysis together with context voting to find the appropriate concept of the instance. The experiments demonstrate that this approach compared to similarity approach yields higher accuracy for instance classification. In sum, the system achieves higher accuracy when the lexical ontology contains a lot of concepts, which generally occurs in practical problems. |
| Starting Page | 66 |
| Ending Page | 70 |
| File Size | 413103 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424455850 |
| e-ISBN | 9781424455867 |
| DOI | 10.1109/ICCAE.2010.5451997 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-02-26 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ontologies Information retrieval Lexical Ontology Information technology Information analysis Instance Classification Databases Voting Training data Latent Semantic Analysis Motion pictures Computational linguistics Artificial intelligence |
| Content Type | Text |
| Resource Type | Article |
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