Development of Multi-Agent-based Intelligent Information Retrieval System
| Project/Area Number |
16500082
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | KYUSHU UNIVERCITY |
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Principal Investigator |
MINE Tsunenori Kyushu University, Faculty of ISEE, Associate Professor, 大学院システム情報科学研究院, 助教授 (30243851)
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| Co-Investigator(Kenkyū-buntansha) |
AMAMIYA Makoto Kyushu University, Faculty of ISEE, Professor, 大学院システム情報科学研究院, 特任教授 (90202697)
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| Project Period (FY) |
2004 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2006: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2005: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 2004: ¥1,100,000 (Direct Cost: ¥1,100,000)
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| Keywords | Peer to Peer / Distributed Information Retrieval / Multi-Agents / Collaborative Filtering / Information Recommendation / Personalization / Semantic Web / Active Browsing / _P2P / 情報フィルタリング / Web / 個人特化型検索 |
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| Research Abstract |
In this research, we first proposed the agent-community-based peer-to-peer information retrieval (ACP2P) method and carried out various experiments. The ACP2P method uses agent communities to manage and look up information of interest to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. Retrieving information relevant to a user query is performed with content files which consist of original and retrieved documents, and two histories : a query/retrieved document history and a query/sender agent history. Making use of the histories have a collaborative filtering effect, which gradually creates virtual agent communities, where agents with the same interests stay together. Our hypothesis is that a virtual agent community reduces communication loads necessary to perform a search. As an agent receives more queries, then m
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ore links to new knowledge are acquired. From this behavior, a "give and take"(or positive feedback) effect for agents seems to emerge.
Secondly, we proposed a conceptual architecture for a personal semantic Web information retrieval system. It incorporates semantic Web, Web service, P2P and multi-agent technologies to enable not only precise location of Web resources but also the automatic or semi-automatic integration of Web resources delivered through Web contents and Web services. In this architecture, the semantic issues concerning the whole lifecycle of information retrieval were considered consistently and the integration of Web contents and Web services is enabled seamlessly. The architecture consists of three main components : consumer, provider and mediator. All providers and consumers are constructed as semantic "MyPortal" which provides a gateway to all the information relevant to a user. Each provider describes its capabilities in what we call a WSCD (Web site capability description), and each consumer will submit relevant queries based on user requirements when a Web search is necessary. The mediator is composed of agents assigned to the consumer and providers using an Agent-Community-based P2P information retrieval (ACP2P) method to fulfill the information sharing among semantic MyPortals. Some of preliminary experimental results showed the efficiency of the ACP2P method and the usefulness of two query/response histories for looking up new information sources and for reducing communication loads.
Lastly, we proposed the Active Browsing system which supports user's Web browsing activity. The system observes user's Web browsing behaviors, learns his/her ways or preferences and tries to save his/her labor for reaching the pages he/she wants by recommending them. The system recommends not only the pages the user browsed in the past, but also the pages which are new and interesting to him/her by collecting from other users with a collaborative-filtering technique. The system is implemented based on Multi-Agent KODAMA framework. Some of preliminary experimental results illustrated the validity of our approach. Less
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Report
(4 results)
Research Products
(41 results)
