NDLI: Online annotation of text streams with structured entities

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Online annotation of text streams with structured entities

Content Provider	ACM Digital Library
Author	Hassanzadeh, Oktie Pu, Ken Q. Drake, Richard Miller, Renée J.
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.
Starting Page	29
Ending Page	38
Page Count	10
File Format	PDF
ISBN	9781450300995
DOI	10.1145/1871437.1871446
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-10-26
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Entity Online Annotation Text stream
Content Type	Text
Resource Type	Article

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