TY - GEN
T1 - Evaluating the helpfulness of linked entities to readers
AU - Yamada, Ikuyai
AU - Ito, Tomotaka
AU - Usami, Shinnosuke
AU - Takagi, Shinsuke
AU - Takeda, Hideaki
AU - Takefuji, Yoshiyasu
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014
Y1 - 2014
N2 - When we encounter an interesting entity (e.g., a person's name or a geographic location) while reading text, we typically search and retrieve relevant information about it. Entity linking (EL) is the task of linking entities in a text to the corresponding entries in a knowledge base, such as Wikipedia. Recently, EL has received considerable attention. EL can be used to enhance a user's text reading experience by streamlining the process of retrieving information on entities. Several EL methods have been proposed, though they tend to extract all of the entities in a document including unnecessary ones for users. Excessive linking of entities can be distracting and degrade the user experience. In this paper, we propose a new method for evaluating the helpfulness of linking entities to users. We address this task using supervised machine-learning with a broad set of features. Experimental results show that our method significantly outperforms baseline methods by approximately 5.7%-12% F1. In addition, we propose an application, Linkify, which enables developers to integrate EL easily into their web sites.
AB - When we encounter an interesting entity (e.g., a person's name or a geographic location) while reading text, we typically search and retrieve relevant information about it. Entity linking (EL) is the task of linking entities in a text to the corresponding entries in a knowledge base, such as Wikipedia. Recently, EL has received considerable attention. EL can be used to enhance a user's text reading experience by streamlining the process of retrieving information on entities. Several EL methods have been proposed, though they tend to extract all of the entities in a document including unnecessary ones for users. Excessive linking of entities can be distracting and degrade the user experience. In this paper, we propose a new method for evaluating the helpfulness of linking entities to users. We address this task using supervised machine-learning with a broad set of features. Experimental results show that our method significantly outperforms baseline methods by approximately 5.7%-12% F1. In addition, we propose an application, Linkify, which enables developers to integrate EL easily into their web sites.
KW - entity linking
KW - knowledge base
KW - wikipedia
UR - http://www.scopus.com/inward/record.url?scp=84907384181&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84907384181&partnerID=8YFLogxK
U2 - 10.1145/2631775.2631802
DO - 10.1145/2631775.2631802
M3 - Conference contribution
AN - SCOPUS:84907384181
SN - 9781450329545
T3 - HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
SP - 169
EP - 178
BT - HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
PB - Association for Computing Machinery
T2 - 25th ACM Conference on Hypertext and Social Media, HT 2014
Y2 - 1 September 2014 through 4 September 2014
ER -