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TAGME: on-the-fly annotation of short text fragments (by wikipedia entities)

Authors:

Paolo Ferragina and

Ugo ScaiellaAuthors Info & Claims

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

October 2010

Pages 1625 - 1628

https://doi.org/10.1145/1871437.1871689

Published: 26 October 2010 Publication History

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Abstract

We designed and implemented TAGME, a system that is able to efficiently and judiciously augment a plain-text with pertinent hyperlinks to Wikipedia pages. The specialty of TAGME with respect to known systems [5,8] is that it may annotate texts which are short and poorly composed, such as snippets of search-engine results, tweets, news, etc. This annotation is extremely informative, so any task that is currently addressed using the bag-of-words paradigm could benefit from using this annotation to draw upon (the millions of) Wikipedia pages and their inter-relations.

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P. Ferragina and A. Gulli. A personalized search engine based on web-snippet hierarchical clustering. Softw. Pract. & Exper., 38(2): 189--225, 2008.

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P. Ferragina and U. Scaiella. TAGME: On-the-fly annotation of short text fragents (by Wikipedia entities). Available on http://arxiv.org/abs/1006.3498.

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Cited By

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Bulathwela SPérez-Ortiz MHolloway CCukurova MShawe-Taylor J(2024)Artificial Intelligence Alone Will Not Democratise Education: On Educational Inequality, Techno-Solutionism and Inclusive ToolsSustainability10.3390/su1602078116:2(781)Online publication date: 16-Jan-2024
https://doi.org/10.3390/su16020781
何迈(2024)Research on Fake News Detection Method Using Heterogeneous Graph Fusion with Background KnowledgeComputer Science and Application10.12677/csa.2024.14306814:03(178-185)Online publication date: 2024
https://doi.org/10.12677/csa.2024.143068
Deng ZDou ZSu ZWen J(2024)Multi-grained Document Modeling for Search Result DiversificationACM Transactions on Information Systems10.1145/365285242:5(1-22)Online publication date: 27-Apr-2024
https://dl.acm.org/doi/10.1145/3652852
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Index Terms

TAGME: on-the-fly annotation of short text fragments (by wikipedia entities)
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Information systems
  1. Information retrieval
    1. Document representation

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Published In

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

October 2010

2036 pages

ISBN:9781450300995

DOI:10.1145/1871437

General Chair:
Jimmy Huang
York University, Canada
,
Program Chairs:
Nick Koudas
University of Toronto, Canada
,
Gareth Jones
Dublin City University, Ireland
,
Xindong Wu
University of Vermont, USA
,
Kevyn Collins-Thompson
Microsoft Research, USA
,
Aijun An
York University, Canada

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Association for Computing Machinery

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Published: 26 October 2010

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CIKM '10: International Conference on Information and Knowledge Management

October 26 - 30, 2010

ON, Toronto, Canada

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https://doi.org/10.3390/su16020781
何迈(2024)Research on Fake News Detection Method Using Heterogeneous Graph Fusion with Background KnowledgeComputer Science and Application10.12677/csa.2024.14306814:03(178-185)Online publication date: 2024
https://doi.org/10.12677/csa.2024.143068
Deng ZDou ZSu ZWen J(2024)Multi-grained Document Modeling for Search Result DiversificationACM Transactions on Information Systems10.1145/365285242:5(1-22)Online publication date: 27-Apr-2024
https://dl.acm.org/doi/10.1145/3652852
Yuan XLiu KWang Y(2024)Contrastive Language-knowledge Graph Pre-trainingACM Transactions on Asian and Low-Resource Language Information Processing10.1145/364482023:4(1-21)Online publication date: 9-Feb-2024
https://dl.acm.org/doi/10.1145/3644820
Kaiser MSaha Roy RWeikum GAngélica LLattanzi SMuñoz Medina AAkoglu LGionis AVassilvitskii S(2024)Robust Training for Conversational Question Answering Models with Reinforced Reformulation GenerationProceedings of the 17th ACM International Conference on Web Search and Data Mining10.1145/3616855.3635822(322-331)Online publication date: 4-Mar-2024
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