On the Automatic Extracting and Matching of Object Features Between Expertise Corpus and Oral Description－A Study Based on the Expert Corpus of Birds
碩士 === 長榮大學 === 資訊管理學系碩士班 === 95 === The representation of object features is an important task in pattern recognition, information retrieval and interactive query, etc. This paper addresses how to utilize computational linguistics and fuzzy set techniques to automatically establish the knowledge ba...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2007
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| Online Access: | http://ndltd.ncl.edu.tw/handle/8d5385 |
| Summary: | 碩士 === 長榮大學 === 資訊管理學系碩士班 === 95 === The representation of object features is an important task in pattern recognition, information retrieval and interactive query, etc. This paper addresses how to utilize computational linguistics and fuzzy set techniques to automatically establish the knowledge base for semi-structural domain expertise.
First, we use a wild bird illustrated book as the training corpus and established the key-feature frame of the domain expertise. Then, we extract features of the objects and encode lexical and fuzzification vectors according to fuzzy set theory. In the experiment, we calculate the similarity between training and testing corpus. The testing corpus includes sentences from another book and user descriptions.
The preliminary results show that the Top-10 precision and inclusion ratio reach 72.5% and respectively. The results encourage us that the proposed approach is suitable for the representation and query of domain expertise. The future works will be focus on promoting the precision ratio by integrating more sophisticate approaches for the representation and matching of oral description.
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