Linking Fine-Grained Locations in User Comments (Extended Abstract)

Many domain-specific websites host a profile page for each entity (e.g., locations on Foursquare, movies on IMDb, and products on Amazon), and users can post comments on it. When commenting on an entity, users often mention other entities for reference or comparison. Compared with web pages and twee...

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Bibliographic Details
Published in2018 IEEE 34th International Conference on Data Engineering (ICDE) pp. 1763 - 1764
Main Authors Jialong Han, Aixin Sun, Gao Cong, Xin Zhao, Wayne, Zongcheng Ji, Phan, Minh C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2018
Subjects
Buildings
Data engineering
Entity Linking
Knowledge Graph
LSBN
Probabilistic logic
Roads
Sun
Task analysis
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Summary:Many domain-specific websites host a profile page for each entity (e.g., locations on Foursquare, movies on IMDb, and products on Amazon), and users can post comments on it. When commenting on an entity, users often mention other entities for reference or comparison. Compared with web pages and tweets, disambiguating the mentioned entities in user comments has not received much attention. This paper investigates linking fine-grained locations in Foursquare comments. We demonstrate that the focal location, i.e., the location that a comment is posted on, provides rich contexts for linking. To exploit such information, we represent the Foursquare data in a graph, which includes locations, comments, and their relations. A probabilistic model named FocalLink is proposed to estimate the probability that a user mentions a location when commenting on a focal location, by following different kinds of relations. Experimental results show that FocalLink is consistently superior to different baselines.
ISSN:2375-026X
DOI:10.1109/ICDE.2018.00239