A Verification Method of Hyponymy between Chinese Terms Based on Concept Space

Liu, Lei; Zhang, Sen; Diao, Lu Hong; Yan, Shaomin; Cao, Cun Gen

doi:10.1007/978-3-642-04875-3_20

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Thus, when the researchers use concepts rather than single terms they try to express implicit senses that are not given by isolated terms, therefore a concept is represented as a set of adjacent terms. Liu et al (2009) proposed a sense recognition of hyponyms based on concept space. They used the contexts of hyponyms and the weights of feature words to construct a hyponyms-word vector space.…”

Section: Concept-based Methodsmentioning

confidence: 99%

Hybrid Query Expansion Model Based on Pseudo Relevance Feedback and Semantic Tree for Arabic IR

Mazari

Djeffal

2021

International Journal of Information Retrieval Research

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In this paper, the authors propose and readapt a new concept-based approach of query expansion in the context of Arabic information retrieval. The purpose is to represent the query by a set of weighted concepts in order to identify better the user's information need. Firstly, concepts are extracted from the initially retrieved documents by the Pseudo-Relevance Feedback method, and then they are integrated into a semantic weighted tree in order to detect more information contained in the related concepts connected by semantic relations to the primary concepts. The authors use the “Arabic WordNet” as a resource to extract, disambiguate concepts and build the semantic tree. Experimental results demonstrate that measure of MAP (Mean Average Precision) is about 10% of improvement using the open source Lucene as IR System on a collection formed from the Arabic BBC news.

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Section: Concept-based Methodsmentioning

confidence: 99%

Hybrid Query Expansion Model Based on Pseudo Relevance Feedback and Semantic Tree for Arabic IR

Mazari

Djeffal

2021

International Journal of Information Retrieval Research

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show abstract

“…Firstly we initially acquire a set of candidate hyponymy relation from large Chinese free text based on Chinese lexico-syntactic patterns. Then we build concept space using those candidate hyponymy relations [13] [14]. is not an isolated edge, (c 1 , c 2 ) is denoted by adjacent edge.…”

Section: A Building Concept Spacementioning

confidence: 99%

Spatial Structure Analysis and Identification of Candidate Hyponymy Relations

Liu¹,

Diao²

2013

JSW

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Automatic acquisition of semantic relations is an important problem in knowledge acquisition. We present a method of spatial structure analysis of candidate Chinese hyponymy based on concept space and use them to identify candidate hyponymy. Firstly a group of candidate hyponymy relations is imported into concept space. Secondly we analyze the basic spatial structure of concept space including concept nodes and relation edges. More identified features based on the spatial structure analysis are given and used to identify hyponymy relations. Experimental results show that the spatial structure is very useful to the identification of hyponymy.

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A Verification Method of Hyponymy between Chinese Terms Based on Concept Space

Cited by 2 publications

References 2 publications

Hybrid Query Expansion Model Based on Pseudo Relevance Feedback and Semantic Tree for Arabic IR

Hybrid Query Expansion Model Based on Pseudo Relevance Feedback and Semantic Tree for Arabic IR

Spatial Structure Analysis and Identification of Candidate Hyponymy Relations

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