Name
Abstract | ||
|---|---|---|
Locations, e.g., countries, states, cities, and point-of-interests, are central to news, emergency events, and people's daily lives. Automatic identification of locations associated with or mentioned in documents has been explored for decades. As one of the most popular online social network platforms, Twitter has attracted a large number of users who send millions of tweets on daily basis. Due to... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TKDE.2018.2807840 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | DocType | Volume |
Twitter,Urban areas,Noise measurement,Geology,Task analysis | Journal | 30 |
Issue | ISSN | Citations |
9 | 1041-4347 | 16 |
PageRank | References | Authors |
0.57 | 88 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Zheng | 1 | 19 | 2.33 |
| Jialong Han | 2 | 97 | 8.65 |
| Aixin Sun | 3 | 3071 | 156.89 |