Difference between revisions of "A Model for Ranking Entities and Its Application to Wikipedia"
(Infobox) |
(cat.) |
||
(One intermediate revision by one other user not shown) | |||
Line 10: | Line 10: | ||
== Overview == | == Overview == | ||
Entity Ranking (ER) is a recently emerging search task in Information Retrieval, where the goal is not finding documents matching the query words, but instead finding entities which match types and attributes mentioned in the query. In this paper authors propose a formal model to define entities as well as a complete ER system, providing examples of its application to enterprise, Web, and [[Wikipedia]] scenarios. Since searching for entities on Web scale repositories is an open challenge as the effectiveness of ranking is usually not satisfactory, authors present a set of algorithms based on model and evaluate their retrieval effectiveness. The results show that combining simple Link Analysis, [[Natural Language Processing]], and Named Entity Recognition methods improves retrieval performance of entity search by over 53% for P@10 and 35% for MAP. | Entity Ranking (ER) is a recently emerging search task in Information Retrieval, where the goal is not finding documents matching the query words, but instead finding entities which match types and attributes mentioned in the query. In this paper authors propose a formal model to define entities as well as a complete ER system, providing examples of its application to enterprise, Web, and [[Wikipedia]] scenarios. Since searching for entities on Web scale repositories is an open challenge as the effectiveness of ranking is usually not satisfactory, authors present a set of algorithms based on model and evaluate their retrieval effectiveness. The results show that combining simple Link Analysis, [[Natural Language Processing]], and Named Entity Recognition methods improves retrieval performance of entity search by over 53% for P@10 and 35% for MAP. | ||
+ | |||
+ | == Embed == | ||
+ | === Wikipedia Quality === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | Demartini, Gianluca; Firan, Claudiu S.; Iofciu, Tereza; Krestel, Ralf; Nejdl, Wolfgang. (2008). "[[A Model for Ranking Entities and Its Application to Wikipedia]]".DOI: 10.1109/LA-WEB.2008.8. | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | === English Wikipedia === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | {{cite journal |last1=Demartini |first1=Gianluca |last2=Firan |first2=Claudiu S. |last3=Iofciu |first3=Tereza |last4=Krestel |first4=Ralf |last5=Nejdl |first5=Wolfgang |title=A Model for Ranking Entities and Its Application to Wikipedia |date=2008 |doi=10.1109/LA-WEB.2008.8 |url=https://wikipediaquality.com/wiki/A_Model_for_Ranking_Entities_and_Its_Application_to_Wikipedia}} | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | === HTML === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | Demartini, Gianluca; Firan, Claudiu S.; Iofciu, Tereza; Krestel, Ralf; Nejdl, Wolfgang. (2008). &quot;<a href="https://wikipediaquality.com/wiki/A_Model_for_Ranking_Entities_and_Its_Application_to_Wikipedia">A Model for Ranking Entities and Its Application to Wikipedia</a>&quot;.DOI: 10.1109/LA-WEB.2008.8. | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | |||
+ | |||
+ | [[Category:Scientific works]] |
Latest revision as of 00:48, 22 January 2021
Authors | Gianluca Demartini Claudiu S. Firan Tereza Iofciu Ralf Krestel Wolfgang Nejdl |
---|---|
Publication date | 2008 |
DOI | 10.1109/LA-WEB.2008.8 |
Links | Original |
A Model for Ranking Entities and Its Application to Wikipedia - scientific work related to Wikipedia quality published in 2008, written by Gianluca Demartini, Claudiu S. Firan, Tereza Iofciu, Ralf Krestel and Wolfgang Nejdl.
Overview
Entity Ranking (ER) is a recently emerging search task in Information Retrieval, where the goal is not finding documents matching the query words, but instead finding entities which match types and attributes mentioned in the query. In this paper authors propose a formal model to define entities as well as a complete ER system, providing examples of its application to enterprise, Web, and Wikipedia scenarios. Since searching for entities on Web scale repositories is an open challenge as the effectiveness of ranking is usually not satisfactory, authors present a set of algorithms based on model and evaluate their retrieval effectiveness. The results show that combining simple Link Analysis, Natural Language Processing, and Named Entity Recognition methods improves retrieval performance of entity search by over 53% for P@10 and 35% for MAP.
Embed
Wikipedia Quality
Demartini, Gianluca; Firan, Claudiu S.; Iofciu, Tereza; Krestel, Ralf; Nejdl, Wolfgang. (2008). "[[A Model for Ranking Entities and Its Application to Wikipedia]]".DOI: 10.1109/LA-WEB.2008.8.
English Wikipedia
{{cite journal |last1=Demartini |first1=Gianluca |last2=Firan |first2=Claudiu S. |last3=Iofciu |first3=Tereza |last4=Krestel |first4=Ralf |last5=Nejdl |first5=Wolfgang |title=A Model for Ranking Entities and Its Application to Wikipedia |date=2008 |doi=10.1109/LA-WEB.2008.8 |url=https://wikipediaquality.com/wiki/A_Model_for_Ranking_Entities_and_Its_Application_to_Wikipedia}}
HTML
Demartini, Gianluca; Firan, Claudiu S.; Iofciu, Tereza; Krestel, Ralf; Nejdl, Wolfgang. (2008). "<a href="https://wikipediaquality.com/wiki/A_Model_for_Ranking_Entities_and_Its_Application_to_Wikipedia">A Model for Ranking Entities and Its Application to Wikipedia</a>".DOI: 10.1109/LA-WEB.2008.8.