Context sensitive text mining and belief revision for adaptive information retrieval

R. Y K Lau

doi:10.1109/WI.2003.1241202

Context sensitive text mining and belief revision for adaptive information retrieval

R. Y K Lau

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

7 Citations (Scopus)

Abstract

Autonomous information agents alleviate the information overload problem on the Internet. The AGM belief revision framework provides a rigorous foundation to develop adaptive information agents. The expressive power of the belief revision logic allow a user's information preferences and contextual knowledge of a retrieval situation to be captured and reasoned about within a single logical framework. Contextual knowledge for information retrieval can be acquired via context sensitive text mining. We illustrate a novel approach of integrating the proposed text mining method into the belief revision based adaptive information agents to improve the agents' learning autonomy and prediction power.

Original language	English
Title of host publication	Proceedings - IEEE/WIC International Conference on Web Intelligence, WI 2003
Publisher	IEEE
Pages	256-262
ISBN (Print)	0769519326, 9780769519326
DOIs	https://doi.org/10.1109/WI.2003.1241202
Publication status	Published - 2003
Externally published	Yes
Event	IEEE/WIC International Conference on Web Intelligence, WI 2003 - Halifax, Canada Duration: 13 Oct 2003 → 17 Oct 2003 https://ieeexplore.ieee.org/xpl/conhome/8792/proceeding

Conference

Conference	IEEE/WIC International Conference on Web Intelligence, WI 2003
Place	Canada
City	Halifax
Period	13/10/03 → 17/10/03
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8792/proceeding

Research Keywords

Australia
Databases
Electronic mail
Information retrieval
Information technology
Internet
Output feedback
Search engines
Technological innovation
Text mining

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10.1109/WI.2003.1241202

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title = "Context sensitive text mining and belief revision for adaptive information retrieval",

abstract = "Autonomous information agents alleviate the information overload problem on the Internet. The AGM belief revision framework provides a rigorous foundation to develop adaptive information agents. The expressive power of the belief revision logic allow a user's information preferences and contextual knowledge of a retrieval situation to be captured and reasoned about within a single logical framework. Contextual knowledge for information retrieval can be acquired via context sensitive text mining. We illustrate a novel approach of integrating the proposed text mining method into the belief revision based adaptive information agents to improve the agents' learning autonomy and prediction power.",

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author = "Lau, \{R. Y K\}",

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language = "English",

isbn = "0769519326",

pages = "256--262",

booktitle = "Proceedings - IEEE/WIC International Conference on Web Intelligence, WI 2003",

publisher = "IEEE",

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AB - Autonomous information agents alleviate the information overload problem on the Internet. The AGM belief revision framework provides a rigorous foundation to develop adaptive information agents. The expressive power of the belief revision logic allow a user's information preferences and contextual knowledge of a retrieval situation to be captured and reasoned about within a single logical framework. Contextual knowledge for information retrieval can be acquired via context sensitive text mining. We illustrate a novel approach of integrating the proposed text mining method into the belief revision based adaptive information agents to improve the agents' learning autonomy and prediction power.

KW - Australia

KW - Databases

KW - Electronic mail

KW - Information retrieval

KW - Information technology

KW - Internet

KW - Output feedback

KW - Search engines

KW - Technological innovation

KW - Text mining

UR - https://www.scopus.com/pages/publications/17444409219

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-17444409219&origin=recordpage

U2 - 10.1109/WI.2003.1241202

DO - 10.1109/WI.2003.1241202

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0769519326

SN - 9780769519326

SP - 256

EP - 262

BT - Proceedings - IEEE/WIC International Conference on Web Intelligence, WI 2003

PB - IEEE

T2 - IEEE/WIC International Conference on Web Intelligence, WI 2003

Y2 - 13 October 2003 through 17 October 2003

ER -

Context sensitive text mining and belief revision for adaptive information retrieval

Abstract

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Research Keywords

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