Entity Ranking in Wikipedia
Authors | Anne-Marie Vercoustre James A. Thom Jovan Pehcevski |
|---|---|
Publication date | 2008 |
DOI | 10.1145/1363686.1363943 |
Links | Original Preprint |
Entity Ranking in Wikipedia - scientific work related to Wikipedia quality published in 2008, written by Anne-Marie Vercoustre, James A. Thom and Jovan Pehcevski.
Overview
The traditional entity extraction problem lies in the ability of extracting named entities from plain text using natural language processing techniques and intensive training from large document collections. Examples of named entities include organisations, people, locations, or dates. There are many research activities involving named entities; authors are interested in entity ranking in the field of information retrieval. In this paper, authors describe approach to identifying and ranking entities from the INEX Wikipedia document collection. Wikipedia offers a number of interesting features for entity identification and ranking that authors first introduce. Authors then describe the principles and the architecture of entity ranking system, and introduce methodology for evaluation. Authors preliminary results show that the use of categories and the link structure of Wikipedia, together with entity examples, can significantly improve retrieval effectiveness.
Embed
Wikipedia Quality
Vercoustre, Anne-Marie; Thom, James A.; Pehcevski, Jovan. (2008). "[[Entity Ranking in Wikipedia]]".DOI: 10.1145/1363686.1363943.
English Wikipedia
{{cite journal |last1=Vercoustre |first1=Anne-Marie |last2=Thom |first2=James A. |last3=Pehcevski |first3=Jovan |title=Entity Ranking in Wikipedia |date=2008 |doi=10.1145/1363686.1363943 |url=https://wikipediaquality.com/wiki/Entity_Ranking_in_Wikipedia}}
HTML
Vercoustre, Anne-Marie; Thom, James A.; Pehcevski, Jovan. (2008). "<a href="https://wikipediaquality.com/wiki/Entity_Ranking_in_Wikipedia">Entity Ranking in Wikipedia</a>".DOI: 10.1145/1363686.1363943.
