Search (4 results, page 1 of 1)

  • × author_ss:"Hui, S.C."
  1. Goh, A.; Hui, S.C.: TES: a text extraction system (1996) 0.02
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    Date
    26. 2.1997 10:22:43
  2. Hui, S.C.; Lau, K.L.: ¬An application of neural networks in document retrieval (1997) 0.01
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    Source
    New review of applied expert systems. 1997, no.3, S.69-80
  3. Tho, Q.T.; Hui, S.C.; Fong, A.C.M.: ¬A citation-based document retrieval system for finding research expertise (2007) 0.01
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    Abstract
    Current citation-based document retrieval systems generally offer only limited search facilities, such as author search. In order to facilitate more advanced search functions, we have developed a significantly improved system that employs two novel techniques: Context-based Cluster Analysis (CCA) and Context-based Ontology Generation frAmework (COGA). CCA aims to extract relevant information from clusters originally obtained from disparate clustering methods by building relationships between them. The built relationships are then represented as formal context using the Formal Concept Analysis (FCA) technique. COGA aims to generate ontology from clusters relationship built by CCA. By combining these two techniques, we are able to perform ontology learning from a citation database using clustering results. We have implemented the improved system and have demonstrated its use for finding research domain expertise. We have also conducted performance evaluation on the system and the results are encouraging.
  4. Foo, S.; Hui, S.C.; Lim, H.K.; Hui, L.: Automated thesaurus for enhanced Chinese text retrieval (2000) 0.01
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    Abstract
    Asian languages such as Japanese, Korean and in particular Chinese, are beginning to gain popularity in the information retrieval (IR) domain. The quality of IR systems has traditionally been judged by the system's retrieval effectiveness which, in turn, is commonly measured by data recall and data precision. This paper proposes and describes a process for generating an automatic Chinese thesaurus that can be used to provide related terms to a user's queries to enhance retrieval effectiveness. In the absence of existing automatic Chinese thesauri, techniques used in English thesaurus generation have been evaluated and adapted to generate a Chinese equivalent. The automatic thesaurus is generated by computing the co-occurrence values between domain-specific terms found in a document collection. These co-occurrence values are in turn derived from the term and document frequencies of the terms. A set of experiments was subsequently carried out on a document test set to evaluate the applicability of the thesaurus. Results obtained from these experiments confirmed that such an automatic generated thesaurus is able to improve the retrieval effectiveness of a Chinese IR system.