Name
Abstract | ||
|---|---|---|
Information extraction • a lot of information only published in unstructured format→ textual documents Events • happen at specific place and time event = 〈space,time〉 • events can be of different granularities • can be associated with persons Place, time u0026 person information •widely spread in text documents • can be extracted and normalized Huge document collections • same events in different documents • different persons can be associated with same events → persons can share events Objectives |
Year | Venue | Field |
|---|---|---|
2013 | BTW | Information retrieval,Computer science,Information extraction,Correlation |
DocType | Citations | PageRank |
Conference | 1 | 0.42 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Kapp | 1 | 1 | 0.76 |
| Jannik Strötgen | 2 | 492 | 38.20 |
| Michael Gertz | 3 | 325 | 27.07 |