research-article

Online annotation of text streams with structured entities

Authors:

Oktie Hassanzadeh,

Renée J. MillerAuthors Info & Claims

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

Pages 29 - 38

https://doi.org/10.1145/1871437.1871446

Published: 26 October 2010 Publication History

Abstract

We propose a framework and algorithm for annotating unbounded text streams with entities of a structured database. The algorithm allows one to correlate unstructured and dirty text streams from sources such as emails, chats and blogs, to entities stored in structured databases. In contrast to previous work on entity extraction, our emphasis is on performing entity annotation in a completely online fashion. The algorithm continuously extracts important phrases and assigns to them top-k relevant entities. Our algorithm does so with a guarantee of constant time and space complexity for each additional word in the text stream, thus infinite text streams can be annotated. Our framework allows the online annotation algorithm to adapt to changing stream rate by self-adjusting multiple run-time parameters to reduce or improve the quality of annotation for fast or slow streams, respectively. The framework also allows the online annotation algorithm to incorporate query feedback to learn the user preference and personalize the annotation for individual users.

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Cited By

Yin XHuang YZhou BLi ALan LJia Y(2019)Deep Entity Linking via Eliminating Semantic Ambiguity With BERTIEEE Access10.1109/ACCESS.2019.29554987(169434-169445)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2955498
Zhang JLi J(2016)Graph-Based Jointly Modeling Entity Detection and Linking in Domain-Specific AreaKnowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data10.1007/978-981-10-3168-7_15(146-159)Online publication date: 23-Nov-2016
https://doi.org/10.1007/978-981-10-3168-7_15
Zhang JLi JLi XShi YLi JWang Z(2016)Domain-Specific Entity Linking via Fake Named Entity DetectionDatabase Systems for Advanced Applications10.1007/978-3-319-32025-0_7(101-116)Online publication date: 25-Mar-2016
https://doi.org/10.1007/978-3-319-32025-0_7
Show More Cited By

Index Terms

Online annotation of text streams with structured entities
1. Information systems
  1. Information retrieval

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Published In

cover image ACM Conferences

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

Copyright © 2010 ACM.

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]

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Publication History

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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Cited By

Yin XHuang YZhou BLi ALan LJia Y(2019)Deep Entity Linking via Eliminating Semantic Ambiguity With BERTIEEE Access10.1109/ACCESS.2019.29554987(169434-169445)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2955498
Zhang JLi J(2016)Graph-Based Jointly Modeling Entity Detection and Linking in Domain-Specific AreaKnowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data10.1007/978-981-10-3168-7_15(146-159)Online publication date: 23-Nov-2016
https://doi.org/10.1007/978-981-10-3168-7_15
Zhang JLi JLi XShi YLi JWang Z(2016)Domain-Specific Entity Linking via Fake Named Entity DetectionDatabase Systems for Advanced Applications10.1007/978-3-319-32025-0_7(101-116)Online publication date: 25-Mar-2016
https://doi.org/10.1007/978-3-319-32025-0_7
Shen WWang JHan J(2015)Entity Linking with a Knowledge Base: Issues, Techniques, and SolutionsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2014.232702827:2(443-460)Online publication date: 1-Feb-2015
https://doi.org/10.1109/TKDE.2014.2327028
Tsiporkova ETourwé T(2011)Tool support for technology scouting using online sourcesProceedings of the 30th international conference on Advances in conceptual modeling: recent developments and new directions10.5555/2075202.2075266(371-376)Online publication date: 31-Oct-2011
https://dl.acm.org/doi/10.5555/2075202.2075266
Alvanaki FSebastian MRamamritham KWeikum GSellis TMiller RKementsietsidis AVelegrakis Y(2011)EnBlogueProceedings of the 2011 ACM SIGMOD International Conference on Management of data10.1145/1989323.1989473(1271-1274)Online publication date: 12-Jun-2011
https://dl.acm.org/doi/10.1145/1989323.1989473
Tsiporkova ETourwé T(2011)Tool Support for Technology Scouting Using Online SourcesAdvances in Conceptual Modeling. Recent Developments and New Directions10.1007/978-3-642-24574-9_53(371-376)Online publication date: 2011
https://doi.org/10.1007/978-3-642-24574-9_53

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