poster

Ranking very many typed entities on wikipedia

Authors:

Massimiliano Ciaramita,

Giuseppe AttardiAuthors Info & Claims

CIKM '07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management

Pages 1015 - 1018

https://doi.org/10.1145/1321440.1321599

Published: 06 November 2007 Publication History

Get Access

Abstract

We discuss the problem of ranking very many entities of different types. In particular we deal with a heterogeneous set of types, some being very generic and some very specific. We discuss two approaches for this problem: i) exploiting the entity containment graph and ii) using a Web search engine to compute entity relevance. We evaluate these approaches on the real task of ranking Wikipedia entities typed with a state-of-the-art named-entity tagger. Results show that both approaches can greatly increase the performance of methods based only on passage retrieval.

References

[1]

S. Chakrabarti, K. Puniyani, and S. Das. Optimizing scoring functions and indexes for proximity search in type-annotated corpora. In WWW '06, pages 717--726, New York, NY, USA, 2006. ACM Press.

Digital Library

Google Scholar

[2]

H. Chen, H. Shen, J. Xiong, S. Tan, and X. Cheng. Social network structure behind the mailing lists: ICT-IIIS at TREC 2006 expert finding track. In Text REtrieval Conference (TREC), 2006.

Google Scholar

[3]

Ludovic Denoyer and Patrick Gallinari. The wikipedia xml corpus. SIGIR Forum, 40(1):64--69, June 2006.

Digital Library

Google Scholar

[4]

Yutaka Matsuo, Masahiro Hamasaki, Hideaki Takeda, Junichiro Mori, Danushka Bollegara, Yoshiyuki Nakamura, Takuichi Nishimura, Koiti Hasida, and Mitsuru Ishizuka. Spinning Multiple Social Networks for Semantic Web. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI 2006), 2006.

Digital Library

Google Scholar

[5]

Peter Mika. Flink: Semantic Web Technology for the Extraction and Analysis of Social Networks. Journal of Web Semantics, 3(2), 2005.

Digital Library

Google Scholar

[6]

G. Salton. Automatic text processing. Addison-Wesley, Reading, MA, 1989.

Digital Library

Google Scholar

[7]

H. Zaragoza, J. Atserias, M. Ciaramita, and G. Attardi. Semantically annotated snapshot of the English Wikipedia v.0 (SW0).http://www.yr-bcn.es/semanticWikipedia, 2007.

Google Scholar

Cited By

View all

Pouriyeh SAllahyari MLiu QCheng GArabnia HAtzori MMohammadi FKochut K(2019)Ontology Summarization: Graph-Based Methods and BeyondInternational Journal of Semantic Computing10.1142/S1793351X1930001213:02(259-283)Online publication date: 25-Jun-2019
https://doi.org/10.1142/S1793351X19300012
IMRATTANATRAI WKATO MTANAKA KYOSHIKAWA M(2018)Entity Ranking for Queries with Modifiers Based on Knowledge Bases and Web Search ResultsIEICE Transactions on Information and Systems10.1587/transinf.2017EDP7372E101.D:9(2279-2290)Online publication date: 1-Sep-2018
https://doi.org/10.1587/transinf.2017EDP7372
Wang CZhou GHe XZhou A(2018)NERank+Frontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-017-6471-412:3(504-517)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s11704-017-6471-4
Show More Cited By

Index Terms

Ranking very many typed entities on wikipedia
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

Recommendations

Entity ranking using Wikipedia as a pivot
CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

In this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant ...
Discovering Missing Semantic Relations between Entities in Wikipedia
ISWC '13: Proceedings of the 12th International Semantic Web Conference - Part I

Wikipedia's infoboxes contain rich structured information of various entities, which have been explored by the DBpedia project to generate large scale Linked Data sets. Among all the infobox attributes, those attributes having hyperlinks in its values ...
Evaluating Entity Linking with Wikipedia

Named Entity Linking (nel) grounds entity mentions to their corresponding node in a Knowledge Base (kb). Recently, a number of systems have been proposed for linking entity mentions in text to Wikipedia pages. Such systems typically search for candidate ...

Comments

Information & Contributors

Information

Published In

CIKM '07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management

November 2007

1048 pages

ISBN:9781595938039

DOI:10.1145/1321440

Co-chair:
Alberto H. F. Laender,
Conference Chairs:
André O. Falcão
Universidade de Lisboa, Portugal
,
Øystein Haug Olsen,
General Chair:
Mário J. Silva
(Universidade de Lisboa, Portugal)
,
Program Chairs:
Ricardo Baeza-Yates,
Deborah L. McGuinness,
Bjorn Olstad

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2007

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Poster

Conference

CIKM07

Sponsor:

CIKM07: Conference on Information and Knowledge Management

November 6 - 10, 2007

Lisbon, Portugal

Acceptance Rates

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

69
Total Citations
View Citations
1,114
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)0

Reflects downloads up to 03 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Pouriyeh SAllahyari MLiu QCheng GArabnia HAtzori MMohammadi FKochut K(2019)Ontology Summarization: Graph-Based Methods and BeyondInternational Journal of Semantic Computing10.1142/S1793351X1930001213:02(259-283)Online publication date: 25-Jun-2019
https://doi.org/10.1142/S1793351X19300012
IMRATTANATRAI WKATO MTANAKA KYOSHIKAWA M(2018)Entity Ranking for Queries with Modifiers Based on Knowledge Bases and Web Search ResultsIEICE Transactions on Information and Systems10.1587/transinf.2017EDP7372E101.D:9(2279-2290)Online publication date: 1-Sep-2018
https://doi.org/10.1587/transinf.2017EDP7372
Wang CZhou GHe XZhou A(2018)NERank+Frontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-017-6471-412:3(504-517)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s11704-017-6471-4
Plachouras V(2018)Document FieldEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_938(1238-1239)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_938
Bhattacharyya PSpasojevic NBarrett RCummings RAgichtein EGabrilovich E(2017)Global Entity Ranking Across Multiple LanguagesProceedings of the 26th International Conference on World Wide Web Companion10.1145/3041021.3054213(761-762)Online publication date: 3-Apr-2017
https://dl.acm.org/doi/10.1145/3041021.3054213
Katz GRokach L(2017)WikiometricsWorld Wide Web10.1007/s11280-016-0427-820:6(1153-1177)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s11280-016-0427-8
Tonon ACatasta MProkofyev RDemartini GAberer KCudré-Mauroux P(2016)Contextualized ranking of entity types based on knowledge graphsWeb Semantics: Science, Services and Agents on the World Wide Web10.5555/2938782.293886437:C(170-183)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.5555/2938782.2938864
Chang JLee MWang T(2016)Integrating a semantic-based retrieval agent into case-based reasoning systemsComputers in Industry10.1016/j.compind.2015.10.00778:C(29-42)Online publication date: 1-May-2016
https://dl.acm.org/doi/10.1016/j.compind.2015.10.007
Wang CZhang RHe XZhou GZhou A(2016)NERank: Bringing Order to Named Entities from TextsWeb Technologies and Applications10.1007/978-3-319-45814-4_2(15-27)Online publication date: 17-Sep-2016
https://doi.org/10.1007/978-3-319-45814-4_2
Almeida PRocha JBallatore AZipf A(2016)Where the Streets Have Known NamesComputational Science and Its Applications -- ICCSA 201610.1007/978-3-319-42089-9_1(1-12)Online publication date: 1-Jul-2016
https://doi.org/10.1007/978-3-319-42089-9_1
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Entity ranking using Wikipedia as a pivot

Discovering Missing Semantic Relations between Entities in Wikipedia

Evaluating Entity Linking with Wikipedia