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Research of Word Sense Disambiguation Based on Word-sense Category Extending

Author: SunGuangQing
Tutor: LuZhiMao
School: Harbin Engineering University
Course: Computer Software and Theory
Keywords: Natural Language Processing Word Sense Disambiguation Semantic Category Expansion Corpus
CLC: TP391.1
Type: Master's thesis
Year: 2008
Downloads: 94
Quote: 1
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Abstract


Word sense disambiguation is a natural language processing is a key problem to be solved , word sense disambiguation in natural language processing research in many application areas has important theoretical and practical significance , but also in recent years is the computational linguistics and natural language processing a important research topic . In this paper, word sense disambiguation relevant research methods and sources of knowledge WSD was reviewed . For the current word sense disambiguation common problem using a new solution. In recent years, doubling the computer's processing speed and storage capacity increases also makes the statistics-based approach can develop, so in recent years based on statistical methods has also been a rapid development. Dictionaries and corpus is based on statistical methods disambiguation disambiguation common resources , based supervised word sense disambiguation needed corpus for training , to determine the meaning disambiguation information provided . This expansion is selected according to the actual needs of dictionary resources to make it more consistent with the needs of word sense disambiguation . Data is sparse and small probability of meaning has been the word sense disambiguation areas difficult to solve . In order to alleviate a guide word sense disambiguation method of human-annotated corpus heavy labor and data sparseness problem, we were on the ambiguity of words and ambiguous words were synonyms directive extend and expand the scope of the same , in order to improve the efficient use of the existing corpus to solve the problem of data sparseness . By designing experiments to verify the proposed method is effective, this method can be more effective mitigation methods with guide WSD data sparseness problem and the problem of small probability meaning . This approach enables the correct word sense disambiguation rate has improved to some extent , a method for word sense disambiguation research has certain reference value.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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