Logical-linguistic semantic in search engine
Users of search engines often have specific questions which they hope or believe a particular resource can answer. The problem, from the computer system’s perspective, is cognitive understanding of the contents in the source and finding the desired answer. Most of the search engines, with Google on...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
WSEAS
2012
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/24453/1/Logical-Linguistic_Semantic_in_Search_Engine.pdf http://irep.iium.edu.my/24453/ http://www.wseas.us/e-library/conferences/2012/Porto/MAMECTIS/MAMECTIS-38.pdf |
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| Summary: | Users of search engines often have specific questions which they hope or believe a particular resource can answer. The problem, from the computer system’s perspective, is cognitive understanding of the contents in the source and finding the desired answer. Most of the search engines, with Google on the top, able to retrieve most likely relevant information based on a query. But not capable of providing answer to a question due to lack of deduction capability. In order to find a specific answer to a question, the engine needs to understand the information content and able to do deductive reasoning. Conventional information representation models used in the search engines rely on an extensive use of keywords and their frequencies in storing and retrieving information and other characteristic data on specific body of information. It is believed that we need new approaches for the development of future search engines which will be more effective. Semantic model is an alternative to conventional approach. We have proposed logical-linguistic model where logic and linguistic formalism are used in providing mechanism for computer to understand the contents of the source and deduce answers to questions. The capability of deduction is much depended on the knowledge representation framework used. The approach applies semantic analysis in transforming and normalising information from natural language texts into a declarative knowledge based representation of first order predicate logic. Retrieval of relevant information can then be performed through plausible logical implication and answer to query is carried out using a theorem proving technique. This paper elaborates on the model and how it is used in search engine and question answering system as one unified model. |
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