Semantic similarity measure for graph-based sentences
Graphical text representation method attempts to capture the syntactival structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these...
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my.uum.repo.83142013-06-30T08:32:36Z http://repo.uum.edu.my/8314/ Semantic similarity measure for graph-based sentences Kamaruddin, Siti Sakira Yusof, Yuhanis Abu Bakar, Nur Azzah QA76 Computer software Graphical text representation method attempts to capture the syntactival structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the similarity between knowledge represented in the graphs.In this paper, we present semantic similarity measure to compare graph based representation of sentences.The proposed method incorporates computational linguistic method to obtain syntactical information prior to representation with graph representation to support semantic matching.In this paper, we present our idea and initial results on the feasibility of the proposed similarity measurement method. 2013-05-04 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/8314/1/siti.pdf Kamaruddin, Siti Sakira and Yusof, Yuhanis and Abu Bakar, Nur Azzah (2013) Semantic similarity measure for graph-based sentences. In: Second International Conference on Advances in Computer and Information Technology (ACIT), 04 May 2013 - 05 May 2013, Malaysia. http://dx.doi.org/10.3850/978-991-07-6261-2_42 |
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QA76 Computer software Kamaruddin, Siti Sakira Yusof, Yuhanis Abu Bakar, Nur Azzah Semantic similarity measure for graph-based sentences |
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Graphical text representation method attempts to capture the syntactival structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the similarity between knowledge represented in the graphs.In this paper, we present semantic similarity measure to compare graph based representation of sentences.The proposed method incorporates computational linguistic method to obtain syntactical information prior to representation with graph representation to support semantic matching.In this paper, we present our idea and initial results on the feasibility of the proposed similarity measurement method. |
format |
Conference or Workshop Item |
author |
Kamaruddin, Siti Sakira Yusof, Yuhanis Abu Bakar, Nur Azzah |
author_facet |
Kamaruddin, Siti Sakira Yusof, Yuhanis Abu Bakar, Nur Azzah |
author_sort |
Kamaruddin, Siti Sakira |
title |
Semantic similarity measure for graph-based sentences |
title_short |
Semantic similarity measure for graph-based sentences |
title_full |
Semantic similarity measure for graph-based sentences |
title_fullStr |
Semantic similarity measure for graph-based sentences |
title_full_unstemmed |
Semantic similarity measure for graph-based sentences |
title_sort |
semantic similarity measure for graph-based sentences |
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2013 |
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http://repo.uum.edu.my/8314/1/siti.pdf http://repo.uum.edu.my/8314/ http://dx.doi.org/10.3850/978-991-07-6261-2_42 |
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1644279795622608896 |
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13.19449 |