Pinpoint web searching and user modeling on the collaborative kodama agents

Tarek Helmy; Satoshi Amamiya; Makoto Amamiya

doi:10.1007/3-540-44700-8_29

Pinpoint web searching and user modeling on the collaborative kodama agents

Tarek Helmy, Satoshi Amamiya, Makoto Amamiya

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

The primary application domain of Kodama1 is the WWW and its purpose in this application is to assist users to find desired information. Three different categories of Kodama’s agents are introduced here, Web Page Agents, Server Agents, and User Interface Agents. Kodama agents learn and adapt to the User’s Preferences (UP), which may change over time. At the same time, they explore these preferences to get any relevancy with the future queries. These communities of Kodama agents autonomously achieve and update their Interpretation Policies (IP) & UP and cooperate with other agents to retrieve distributed relevant information on the Web. This paper studies ways to model user's interests and shown how these models can be deployed for more effective information retrieval. In terms of adaptation speed, the proposed methods make Kodama system acts as a pinpoint information retrieval system, converges to the user’s interests and adapts to the user’s sudden change of interests. Keywords: Web Data Mining and Analysis, Collaborative Information agents, Web site Management, Adapting to User’s Model.

Original language	English
Title of host publication	Electronic Commerce and Web Technologies - Second International Conference, EC-Web 2001, Proceedings
Editors	Kurt Bauknecht, Sanjay Kumar Madria, Gunther Pernul
Publisher	Springer Verlag
Pages	305-314
Number of pages	10
ISBN (Print)	3540425179
DOIs	https://doi.org/10.1007/3-540-44700-8_29
State	Published - 2001
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2115
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2001.

Keywords

Adapting to user’s model
Collaborative information agents
Web data mining and analysis
Web site management

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/3-540-44700-8_29

Cite this

Helmy, T., Amamiya, S., & Amamiya, M. (2001). Pinpoint web searching and user modeling on the collaborative kodama agents. In K. Bauknecht, S. K. Madria, & G. Pernul (Eds.), Electronic Commerce and Web Technologies - Second International Conference, EC-Web 2001, Proceedings (pp. 305-314). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2115). Springer Verlag. https://doi.org/10.1007/3-540-44700-8_29

Helmy, Tarek ; Amamiya, Satoshi ; Amamiya, Makoto. / Pinpoint web searching and user modeling on the collaborative kodama agents. Electronic Commerce and Web Technologies - Second International Conference, EC-Web 2001, Proceedings. editor / Kurt Bauknecht ; Sanjay Kumar Madria ; Gunther Pernul. Springer Verlag, 2001. pp. 305-314 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Pinpoint web searching and user modeling on the collaborative kodama agents",

abstract = "The primary application domain of Kodama1 is the WWW and its purpose in this application is to assist users to find desired information. Three different categories of Kodama{\textquoteright}s agents are introduced here, Web Page Agents, Server Agents, and User Interface Agents. Kodama agents learn and adapt to the User{\textquoteright}s Preferences (UP), which may change over time. At the same time, they explore these preferences to get any relevancy with the future queries. These communities of Kodama agents autonomously achieve and update their Interpretation Policies (IP) \& UP and cooperate with other agents to retrieve distributed relevant information on the Web. This paper studies ways to model user's interests and shown how these models can be deployed for more effective information retrieval. In terms of adaptation speed, the proposed methods make Kodama system acts as a pinpoint information retrieval system, converges to the user{\textquoteright}s interests and adapts to the user{\textquoteright}s sudden change of interests. Keywords: Web Data Mining and Analysis, Collaborative Information agents, Web site Management, Adapting to User{\textquoteright}s Model.",

keywords = "Adapting to user{\textquoteright}s model, Collaborative information agents, Web data mining and analysis, Web site management",

author = "Tarek Helmy and Satoshi Amamiya and Makoto Amamiya",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.",

year = "2001",

doi = "10.1007/3-540-44700-8\_29",

language = "English",

isbn = "3540425179",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Helmy, T, Amamiya, S & Amamiya, M 2001, Pinpoint web searching and user modeling on the collaborative kodama agents. in K Bauknecht, SK Madria & G Pernul (eds), Electronic Commerce and Web Technologies - Second International Conference, EC-Web 2001, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2115, Springer Verlag, pp. 305-314. https://doi.org/10.1007/3-540-44700-8_29

Pinpoint web searching and user modeling on the collaborative kodama agents. / Helmy, Tarek; Amamiya, Satoshi; Amamiya, Makoto.
Electronic Commerce and Web Technologies - Second International Conference, EC-Web 2001, Proceedings. ed. / Kurt Bauknecht; Sanjay Kumar Madria; Gunther Pernul. Springer Verlag, 2001. p. 305-314 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2115).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Helmy, Tarek

AU - Amamiya, Satoshi

AU - Amamiya, Makoto

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2001.

PY - 2001

Y1 - 2001

N2 - The primary application domain of Kodama1 is the WWW and its purpose in this application is to assist users to find desired information. Three different categories of Kodama’s agents are introduced here, Web Page Agents, Server Agents, and User Interface Agents. Kodama agents learn and adapt to the User’s Preferences (UP), which may change over time. At the same time, they explore these preferences to get any relevancy with the future queries. These communities of Kodama agents autonomously achieve and update their Interpretation Policies (IP) & UP and cooperate with other agents to retrieve distributed relevant information on the Web. This paper studies ways to model user's interests and shown how these models can be deployed for more effective information retrieval. In terms of adaptation speed, the proposed methods make Kodama system acts as a pinpoint information retrieval system, converges to the user’s interests and adapts to the user’s sudden change of interests. Keywords: Web Data Mining and Analysis, Collaborative Information agents, Web site Management, Adapting to User’s Model.

AB - The primary application domain of Kodama1 is the WWW and its purpose in this application is to assist users to find desired information. Three different categories of Kodama’s agents are introduced here, Web Page Agents, Server Agents, and User Interface Agents. Kodama agents learn and adapt to the User’s Preferences (UP), which may change over time. At the same time, they explore these preferences to get any relevancy with the future queries. These communities of Kodama agents autonomously achieve and update their Interpretation Policies (IP) & UP and cooperate with other agents to retrieve distributed relevant information on the Web. This paper studies ways to model user's interests and shown how these models can be deployed for more effective information retrieval. In terms of adaptation speed, the proposed methods make Kodama system acts as a pinpoint information retrieval system, converges to the user’s interests and adapts to the user’s sudden change of interests. Keywords: Web Data Mining and Analysis, Collaborative Information agents, Web site Management, Adapting to User’s Model.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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A2 - Bauknecht, Kurt

A2 - Madria, Sanjay Kumar

A2 - Pernul, Gunther

PB - Springer Verlag

ER -

Helmy T, Amamiya S, Amamiya M. Pinpoint web searching and user modeling on the collaborative kodama agents. In Bauknecht K, Madria SK, Pernul G, editors, Electronic Commerce and Web Technologies - Second International Conference, EC-Web 2001, Proceedings. Springer Verlag. 2001. p. 305-314. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-44700-8_29

Pinpoint web searching and user modeling on the collaborative kodama agents

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this