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Title:
An Approach of Filtering Wrong-Type Entities for Entity Ranking
Author: Zhang, Junsan ; Qu, Youli ; Gong, Shu ; Tian, Shengfeng ; Sun, Haoliang
Keyword: related entity finding ; entity ranking ; type filtering ; wikipedia
Source: IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Issued Date: 2013
Volume: E96D, Issue:1, Pages:163-167
Indexed Type: SCI
Department: [Zhang, Junsan; Qu, Youli; Gong, Shu; Tian, Shengfeng] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China. [Sun, Haoliang] Chinese Acad Sci, Inst Software, Natl Key Lab Integrated Informat Syst, Beijing 100864, Peoples R China.
Abstract: Entity is an important information carrier in Web pages. Users would like to directly get a list of relevant entities instead of a list of documents when they submit a query to the search engine. So the research of related entity finding (REF) is a meaningful work. In this paper we investigate the most important task of REF: Entity Ranking The wrong-type entities which don't belong to the target-entity type will pollute the ranking result. We propose a novel method to filter wrong-type entities. We focus on the acquisition of seed entities and automatically extracting the common Wikipedia categories of target-entity type. Also we demonstrate how to filter wrong-type entities using the proposed model. The experimental results show our method can filter wrong-type entities effectively and improve the results of entity ranking.
English Abstract: Entity is an important information carrier in Web pages. Users would like to directly get a list of relevant entities instead of a list of documents when they submit a query to the search engine. So the research of related entity finding (REF) is a meaningful work. In this paper we investigate the most important task of REF: Entity Ranking The wrong-type entities which don't belong to the target-entity type will pollute the ranking result. We propose a novel method to filter wrong-type entities. We focus on the acquisition of seed entities and automatically extracting the common Wikipedia categories of target-entity type. Also we demonstrate how to filter wrong-type entities using the proposed model. The experimental results show our method can filter wrong-type entities effectively and improve the results of entity ranking.
Language: 英语
WOS ID: WOS:000314079800023
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16960
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Zhang, Junsan,Qu, Youli,Gong, Shu,et al. An Approach of Filtering Wrong-Type Entities for Entity Ranking[J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS,2013-01-01,E96D(1):163-167.
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