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Title: An integrated document retrieval method combining entity annotation and keyword index: A KIM platform implementation
Author: XU Xin ; GUO Jinlong ; HONG Yunjia ; JIN Biyi
Source: Chinese Journal of Library and Information Science
Issued Date: 2013-03-25
Volume: 6, Issue:1, Pages:64-77
Keyword: Ontology ; Semantic annotation ; Semantic retrieval ; Entity retrieval|KIM
Subject: 编辑出版
Corresponding Author: Xu Xin (E-mail:xxu@infor.ecnu.edu.cn)
Abstract:

Purpose: The objective of this paper is to testify the effect of ontology-based semantic annotation on the performance of document retrieval.

Design/methodology/approach: An integrated document retrieval method is put forward in this paper, in which the entities of documents are annotated by the upper ontology and domain ontology, then the documents are further indexed by the entity annotation as well as traditional keywords.

Findings: The research result shows that the structured entity retrieval and relation retrieval can be realized by the ontology-based entity index, which is beyond the ability of the tradition keyword-based retrieval. Meanwhile, the experiment shows that the recall and precision of document retrieval are improved effectively.

Research limitations: Due to the small amount of our current tourism domain ontology, the document retrieval with the ontology-based semantic index is limited by the size of ontology and the precision of semantic annotation. Meanwhile, the semantic annotation algorithm mainly relies on the current information extraction strategy of KIM Platform. Therefore, the performance of disambiguation and relation extraction algorithm need to be further improved.

Practical implications: Our method can improve the efficiency of document retrieval system, which facilitates the knowledge and document management in corporations, governments and other organizations.

Originality/value: The integrated document retrieval method proposed in the paper can combine the entity index based on the general ontology with domain ontology and the keyword index. Our result verified the effectiveness of the combined index strategy.

English Abstract:

Purpose: The objective of this paper is to testify the effect of ontology-based semantic annotation on the performance of document retrieval.

Design/methodology/approach: An integrated document retrieval method is put forward in this paper, in which the entities of documents are annotated by the upper ontology and domain ontology, then the documents are further indexed by the entity annotation as well as traditional keywords.

Findings: The research result shows that the structured entity retrieval and relation retrieval can be realized by the ontology-based entity index, which is beyond the ability of the tradition keyword-based retrieval. Meanwhile, the experiment shows that the recall and precision of document retrieval are improved effectively.

Research limitations: Due to the small amount of our current tourism domain ontology, the document retrieval with the ontology-based semantic index is limited by the size of ontology and the precision of semantic annotation. Meanwhile, the semantic annotation algorithm mainly relies on the current information extraction strategy of KIM Platform. Therefore, the performance of disambiguation and relation extraction algorithm need to be further improved.

Practical implications: Our method can improve the efficiency of document retrieval system, which facilitates the knowledge and document management in corporations, governments and other organizations.

Originality/value: The integrated document retrieval method proposed in the paper can combine the entity index based on the general ontology with domain ontology and the keyword index. Our result verified the effectiveness of the combined index strategy.

Related URLs: 查看原文
Content Type: 期刊论文
URI: http://ir.las.ac.cn/handle/12502/6151
Appears in Collections:Chinese Journal of Library and Information Science-2013_期刊论文

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Recommended Citation:
XU Xin,GUO Jinlong,HONG Yunjia,et al. An integrated document retrieval method combining entity annotation and keyword index: A KIM platform implementation[J]. Chinese Journal of Library and Information Science,2013,6(1):64-77.
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