Abstract
This paper presents an agent community based peer-to-peer information retrieval method called ACP2P method[16] and discusses the experimental results of the method. The ACP2P method uses agent communities to manage and look up information related 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. In order to retrieve information relevant to a user query, an agent uses a content file, which consists of retrieved documents and two histories : a query/retrieved document history(Q/RDH) and a query/sender agent history(Q/SAH). The former is a list of pairs of a query and the address of an agent that returned documents relevant to the query. The latter is a list of pairs of a query and the address of a sender agent and shows “who sent what query to the agent”. This is useful for finding a new information source. Making use of Q/SAH is expected to 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 more links to new knowledge are acquired. From this behavior, a “give and take”(or positive feedback) effect for agents seems to emerge. We implemented this method with Multi-Agent Kodama, and conducted experiments to test the hypothesis. The experimental results showed that the method employing two histories was much more efficient than a naive method employing ’multicast’ techniques only to look up a target agent. Further, making use of Q/SAH facilitates bidirectional communications between agents and thus creates virtual agent communities.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Balabanovic, M., Shoham, Y.: Content-based, collaborative recommendation. Communications of the ACM 40(3), (1997)
Brin, S., Page, L.: The Anatomy of a Large-Scale Hypertextual Web Search Engine. In: Proc. of 7th International World Wide Web Conference:WWW7 Conference (1998)
Callan, J., Connell, M.: Query-based sampling of text databases. ACM Transactions on Information Systems 19(2), 97–130 (2001)
Callan, J., Connell, M., Du, A.: Automatic discovery of language models for text databases. In: ACM SIGMOD, pp. 479–490 (1999)
Clarke, I., Sandberg, O., Wiley, B., Hong, T.W.: Freenet: A distributed anonymous information storage and retrieval system. Designing Privacy Enhancing Technologies: International Workshop on Design Issues in Anonymity and Unobservability (2001), http://www.doc.ic.ac.uk/~twh1/academic/
Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by latent semantic analysis. Journal of the American Society of Information Science (1990)
Gallardo-Antolin, A., et al.: I-Gaia: an information processing layer for the diet platform. In: In the first international joint conference on Autonomous Agents and Multi Agent Systems (AAMAS), vol. 7, pp. 1272–1279 (2002)
Gnutella (2000), http://gnutella.wego.com/
Goldberg, D., Nichols, D., Oki, B.M., Terry, D.: Using collaborative filtering to weave an information tapestry. Communications of the ACM 35, 61–70 (1992)
Good, N., Schafer, J.B., Konstan, J.A., Borchers, A., Sarwar, B.M., Herlocker, J.L., Riedl, J.: Combining collaborative filtering with personal agents for better recommendations. In: AAAI/IAAI, pp. 439–446 (1999)
Herlocker, J.L., Konstan, J.A., Borchers, A., Riedl, J.: An algorithmic framework for performing collaborative filtering. In: SIGIR 1999, pp. 230–237 (1999)
Kanfer, A., Sweet, J., Schlosser, A.: Humanizing the net: Social navigation with a ”know-who” email agent. In: The 3rd Conference on Human Factors & The Web (1997), http://www.ncsa.uiuc.edu/edu/trg
Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. Journal of the ACM 46, 604–632 (1999)
Lang, K.: NewsWeeder: learning to filter netnews. In: Proceedings of the 12th International Conference on Machine Learning, pp. 331–339. Morgan Kaufmann publishers Inc, San Mateo (1995)
Melville, P., Mooney, R.J., Nagarajan, R.: Content-boosted collaborative filtering. In: SIGIR-2001 Workshop on Recommender Systems (2001)
Mine, T., Matsuno, D., Takaki, K., Amamiya, M.: Agent community based peer-to-peer information retrieval. In: The third international joint conference on Autonomous Agents and Multi Agent Systems (AAMAS), vol. 7 (2004); poster
Napster (2000), http://www.napster.com/
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: Grouplens: Open architecture for collaborative filtering of netnews (1994)
Ratnasamy, S., Francis, P., Handley, M., Karp, R., Shenker, S.: A scalable contentaddressable network. SIGCOMM, 161–172 (2001)
Robertson, S.E., Walker, S.: Some simple effective approximations to the 2- poisson model for probabilistic weighted retrieval. In: Proceedings of the 17 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (1994)
Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. WWW 10, 285–295 (2001)
Schafer, J.B., Konstan, J.A., Riedi, J.: Recommender systems in e-commerce. In: ACM Conference on Electronic Commerce, pp. 158–166 (1999)
Shardanand, U., Maes, P.: Social information filtering: Algorithms for automating “word of mouth”. In: Proceedings of ACM CHI 1995 Conference on Human Factors in Computing Systems, vol. 1, pp. 210–217 (1995)
Stoica, I., Morris, R., Karger, D., Kaashoek, M.F., Balakrishnan, H.: Chord: A scalable peer-to-peer lookup service for internet applications. In: Proceedings of the 2001 conference on applications, technologies, architectures, and protocols for computer communications, pp. 149–160 (2001)
Tang, C., Xu, Z., Dwarkadas, S.: Peer-to-peer information retrieval using selforganizing semantic overlay networks. SIGCOMM (2003)
Yahoo (2003), http://www.yahoo.co.jp/
Yang, B., Garcia-Molina, H.: Designing a super-peer network. In: IEEE International Conference on Data Engineering, vol. 3 (2003)
Yimam-Seid, D., Kobsa, A.: Expert finding systems for organizations: Problem and domain analysis and the demoir approach. Journal of Organizational Computing and Electronic Commerce 13(1), 1–24 (2003)
Zhong, G., Amamiya, S., Takahashi, K., Mine, T., Amamiya, M.: The design and application of kodama system. IEICE Transactions INF.& SYST., E85-D 4(04), 637–646 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mine, T., Matsuno, D., Kogo, A., Amamiya, M. (2004). Design and Implementation of Agent Community Based Peer-to-Peer Information Retrieval Method. In: Klusch, M., Ossowski, S., Kashyap, V., Unland, R. (eds) Cooperative Information Agents VIII. CIA 2004. Lecture Notes in Computer Science(), vol 3191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30104-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-30104-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23170-7
Online ISBN: 978-3-540-30104-2
eBook Packages: Springer Book Archive