| 实体搜索综述 |
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| 引用本文： | 张香玲,陈跃国,马登豪,陈峻,杜小勇. 实体搜索综述[J]. 软件学报, 2017, 28(6): 1584-1605 |
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| 作者姓名： | 张香玲 陈跃国 马登豪 陈峻 杜小勇 |
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| 作者单位： | 数据工程与知识工程教育部重点实验室(中国人民大学),北京 100872;中国人民大学 信息学院,北京100872,数据工程与知识工程教育部重点实验室(中国人民大学),北京 100872;中国人民大学 信息学院,北京100872,数据工程与知识工程教育部重点实验室(中国人民大学),北京 100872;中国人民大学 信息学院,北京100872,数据工程与知识工程教育部重点实验室(中国人民大学),北京 100872;中国人民大学 信息学院,北京100872,数据工程与知识工程教育部重点实验室(中国人民大学),北京 100872;中国人民大学 信息学院,北京100872 |
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| 基金项目： | 国家自然科学基金(61472426,61432006) |
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| 摘 要： | 与传统的以网页页面集合的方式呈现搜索结果不同,实体搜索的结果是实体或实体集合,其优点是无需用户在纷杂的网页里面进行二次查找,更能提升用户的搜索体验.实体搜索的任务可以分为相关实体搜索和相似实体搜索.本文对近年来这两类任务的实体搜索技术进行综述.首先给出了实体搜索的形式化的定义,并介绍了常用的评测指标;然后对两种不同形式的实体搜索任务在两类数据源(非结构化数据集和结构化数据集)上的主要研究方法进行详细阐述和对比;最后对未来的研究内容和发展方向进行了探讨和展望.
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| 关 键 词： | 实体搜索 对象搜索 相关实体搜索 相似实体搜索 知识图谱 |
| 收稿时间： | 2016-09-30 |
| 修稿时间： | 2016-11-23 |
Survey on Entity Search |
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| ZHANG Xiang-Ling,CHEN Yue-Guo,MA Deng-Hao,CHEN Jun and DU Xiao-Yong. Survey on Entity Search[J]. Journal of Software, 2017, 28(6): 1584-1605 |
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| Authors: | ZHANG Xiang-Ling CHEN Yue-Guo MA Deng-Hao CHEN Jun DU Xiao-Yong |
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| Affiliation: | Key Laboratory of Data Engineering and Knowledge Engineering, MOE(Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China,Key Laboratory of Data Engineering and Knowledge Engineering, MOE(Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China,Key Laboratory of Data Engineering and Knowledge Engineering, MOE(Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China,Key Laboratory of Data Engineering and Knowledge Engineering, MOE(Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China and Key Laboratory of Data Engineering and Knowledge Engineering, MOE(Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China |
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| Abstract: | Entity search differs from traditional search engines where the results of traditional search engines are Web pages, and the results of entity search are entities which can enhance the user''s search experience. Entity search can be further categorized into the task of related entity search and the task of similar entity search. In this paper, we present a survey on the techniques of entity search. Firstly, entity search is defined formally, and frequently used evaluation measures are introduced as well. Secondly, the algorithms of the two different types of entity search on two different data sources (unstructured data and structured data) are reviewed in details. Finally, open research issues and possible future research directions are discussed. |
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| Keywords: | entity search object search related entity search similar entity search knowledge graph |
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