Linking fine-grained locations in user comments
Many domain-specific websites host a profile page for each entity (e.g., locations on Foursquare, movies on IMDb, and products on Amazon) for users to post comments on. When commenting on an entity, users often mention other entities for reference or comparison. Compared with web pages and tweets, t...
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| Formáid: | Journal Article |
| Teanga: | English |
| Foilsithe / Cruthaithe: |
2019
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| Ábhair: | |
| Rochtain ar líne: | https://hdl.handle.net/10356/86191 http://hdl.handle.net/10220/48310 |
| _version_ | 1826128397725597696 |
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| author | Han, Jialong Sun, Aixin Cong, Gao Zhao, Wayne Xin Ji, Zongcheng Phan, Minh C. |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Han, Jialong Sun, Aixin Cong, Gao Zhao, Wayne Xin Ji, Zongcheng Phan, Minh C. |
| author_sort | Han, Jialong |
| collection | NTU |
| description | Many domain-specific websites host a profile page for each entity (e.g., locations on Foursquare, movies on IMDb, and products on Amazon) for users to post comments on. When commenting on an entity, users often mention other entities for reference or comparison. Compared with web pages and tweets, the problem of 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 the linking task. 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 under different collective linking settings. |
| first_indexed | 2024-10-01T07:24:19Z |
| format | Journal Article |
| id | ntu-10356/86191 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:24:19Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/861912020-03-07T11:48:54Z Linking fine-grained locations in user comments Han, Jialong Sun, Aixin Cong, Gao Zhao, Wayne Xin Ji, Zongcheng Phan, Minh C. School of Computer Science and Engineering Entity Linking Named Entity Recognition DRNTU::Engineering::Computer science and engineering Many domain-specific websites host a profile page for each entity (e.g., locations on Foursquare, movies on IMDb, and products on Amazon) for users to post comments on. When commenting on an entity, users often mention other entities for reference or comparison. Compared with web pages and tweets, the problem of 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 the linking task. 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 under different collective linking settings. MOE (Min. of Education, S’pore) Accepted version 2019-05-22T03:10:02Z 2019-12-06T16:17:42Z 2019-05-22T03:10:02Z 2019-12-06T16:17:42Z 2017 Journal Article Han, J., Sun, A., Cong, G., Zhao, W. X., Ji, Z., & Phan, M. C. (2018). Linking fine-grained locations in user comments. IEEE Transactions on Knowledge and Data Engineering, 30(1), 59-72. doi:10.1109/TKDE.2017.2758780 1041-4347 https://hdl.handle.net/10356/86191 http://hdl.handle.net/10220/48310 10.1109/TKDE.2017.2758780 en IEEE Transactions on Knowledge and Data Engineering © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TKDE.2017.2758780. 14 p. application/pdf |
| spellingShingle | Entity Linking Named Entity Recognition DRNTU::Engineering::Computer science and engineering Han, Jialong Sun, Aixin Cong, Gao Zhao, Wayne Xin Ji, Zongcheng Phan, Minh C. Linking fine-grained locations in user comments |
| title | Linking fine-grained locations in user comments |
| title_full | Linking fine-grained locations in user comments |
| title_fullStr | Linking fine-grained locations in user comments |
| title_full_unstemmed | Linking fine-grained locations in user comments |
| title_short | Linking fine-grained locations in user comments |
| title_sort | linking fine grained locations in user comments |
| topic | Entity Linking Named Entity Recognition DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/86191 http://hdl.handle.net/10220/48310 |
| work_keys_str_mv | AT hanjialong linkingfinegrainedlocationsinusercomments AT sunaixin linkingfinegrainedlocationsinusercomments AT conggao linkingfinegrainedlocationsinusercomments AT zhaowaynexin linkingfinegrainedlocationsinusercomments AT jizongcheng linkingfinegrainedlocationsinusercomments AT phanminhc linkingfinegrainedlocationsinusercomments |