Updating collection representations for federated search

ABSTRACT

To facilitate the search for relevant information across a setof online distributed collections, a federated information retrieval system typically represents each collection, centrally, by a set of vocabularies or sampled documents. Accurate retrieval is therefore related to how precise each representation reflects the underlying content stored in that collection. As collections evolve over time, collection representations should also be updated to reflect any change, however, a current solution has not yet been proposed. In this study we examine both the implications of out-of-date representation sets on retrieval accuracy, as well as proposing three different policies for managing necessary updates. Each policyis evaluated on a testbed of forty-four dynamic collections over an eight-week period. Our findings show that out-of-date representations significantly degrade performance overtime, however, adopting a suitable update policy can minimise this problem.

REFERENCES

• 1: Thi Truong Avrahami , Lawrence Yau , Luo Si , Jamie Callan, The FedLemur project: Federated search in the real world, Journal of the American Society for Information Science and Technology, v.57 n.3, p.347-358, February 2006 [doi>10.1002/asi.v57:3]
• 2: Baillie, M., Azzopardi, L., and Crestani, F. (2006). Adaptive query-based sampling of distributed collections. In Proc. SPIRE Conf., Glasgow, UK pages 316--328.
• 3: Callan, J. (2000). Advances in information retrieval Chapter 5, Distributed information retrieval, pages 127--150. Kluwer.
• 4: Jamie Callan , Margaret Connell, Query-based sampling of text databases, ACM Transactions on Information Systems (TOIS), v.19 n.2, p.97-130, April 2001 [doi>10.1145/382979.383040]
• 5: James P. Callan , Zhihong Lu , W. Bruce Croft, Searching distributed collections with inference networks, Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval, p.21-28, July 09-13, 1995, Seattle, Washington, United States [doi>10.1145/215206.215328]
• 6: Junghoo Cho , Hector Garcia-Molina, Effective page refresh policies for Web crawlers, ACM Transactions on Database Systems (TODS), v.28 n.4, p.390-426, December 2003 [doi>10.1145/958942.958945]
• 7: Nick Craswell , Peter Bailey , David Hawking, Server selection on the World Wide Web, Proceedings of the fifth ACM conference on Digital libraries, p.37-46, June 02-07, 2000, San Antonio, Texas, United States [doi>10.1145/336597.336628]
• 8: Nick Craswell , Francis Crimmins , David Hawking , Alistair Moffat, Performance and cost tradeoffs in Web search, Proceedings of the 15th Australasian database conference, p.161-169, January 01, 2004, Dunedin, New Zealand
• 9: Luis Gravano , Chen-Chuan K. Chang , Héctor García-Molina , Andreas Paepcke, STARTS: Stanford proposal for Internet meta-searching, Proceedings of the 1997 ACM SIGMOD international conference on Management of data, p.207-218, May 11-15, 1997, Tucson, Arizona, United States
• 10: Luis Gravano , Héctor García-Molina , Anthony Tomasic, GlOSS: text-source discovery over the Internet, ACM Transactions on Database Systems (TODS), v.24 n.2, p.229-264, June 1999 [doi>10.1145/320248.320252]
• 11: Luis Gravano , Panagiotis G. Ipeirotis , Mehran Sahami, QProber: A system for automatic classification of hidden-Web databases, ACM Transactions on Information Systems (TOIS), v.21 n.1, p.1-41, January 2003 [doi>10.1145/635484.635485]
• 12: David Hawking , Paul Thomas, Server selection methods in hybrid portal search, Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, August 15-19, 2005, Salvador, Brazil [doi>10.1145/1076034.1076050]
• 13: Panagiotis G. Ipeirotis , Alexandros Ntoulas , Junghoo Cho , Luis Gravano, Modeling and Managing Content Changes in Text Databases, Proceedings of the 21st International Conference on Data Engineering, p.606-617, April 05-08, 2005 [doi>10.1109/ICDE.2005.91]
• 14: Kleinberg, J. (2006). Temporal dynamics of on-line information systems. Data Stream Management: Processing High-Speed Data Streams.
• 15: S. Kullback. Information theoery and statistics. Wiley, New York, NY 1959.
• 16: Alexandros Ntoulas , Petros Zerfos , Junghoo Cho, Downloading textual hidden web content through keyword queries, Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries, June 07-11, 2005, Denver, CO, USA [doi>10.1145/1065385.1065407]
• 17: Paepcke, A., Brandriff, R., Janee, G., Larson, R.,Ludaescher, B., Melnik, S., and Raghavan, S. (2000). Search middleware and the simple digital library interoperability protocol. D-Lib Magazine 6(3).
• 18: The invisible Web: uncovering information sources search engines can't see, Information Today, Inc., Medford, NJ, 2001
• 19: Robertson, S., Walker, S., Hancock-Beaulieu, M., Gull ,A., and Lau, M. (1992). Okapi at TREC. In Proceedings of TREC-1992, Gaithersburg, MA pages 21--30.
• 20: Luo Si , Jamie Callan, Relevant document distribution estimation method for resource selection, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, July 28-August 01, 2003, Toronto, Canada [doi>10.1145/860435.860490]
• 21: Luo Si , Jamie Callan, A semisupervised learning method to merge search engine results, ACM Transactions on Information Systems (TOIS), v.21 n.4, p.457-491, October 2003 [doi>10.1145/944012.944017]
• 22: Luo Si , Jamie Callan, Unified utility maximization framework for resource selection, Proceedings of the thirteenth ACM international conference on Information and knowledge management, November 08-13, 2004, Washington, D.C., USA [doi>10.1145/1031171.1031180]
• 23: Luo Si , Rong Jin , Jamie Callan , Paul Ogilvie, A language modeling framework for resource selection and results merging, Proceedings of the eleventh international conference on Information and knowledge management, November 04-09, 2002, McLean, Virginia, USA [doi>10.1145/584792.584856]
• 24: Shokouhi, M. (2007). Central-Rank-Based Collection Selection in uncooperative distributed information retrieval. Proc. ECIR Conf., Rome, Italy pages 160--172.
• 25: Milad Shokouhi , Justin Zobel , Saied Tahaghoghi , Falk Scholer, Using query logs to establish vocabularies in distributed information retrieval, Information Processing and Management: an International Journal, v.43 n.1, p.169-180, January 2007 [doi>10.1016/j.ipm.2006.04.003]
• 26: Milad Shokouhi , Justin Zobel , Falk Scholer , S. M. M. Tahaghoghi, Capturing collection size for distributed non-cooperative retrieval, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, August 06-11, 2006, Seattle, Washington, USA [doi>10.1145/1148170.1148227]
• 27: Jinxi Xu , Jamie Callan, Effective retrieval with distributed collections, Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, p.112-120, August 24-28, 1998, Melbourne, Australia [doi>10.1145/290941.290974]
• 28: Jinxi Xu , W. Bruce Croft, Cluster-based language models for distributed retrieval, Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, p.254-261, August 15-19, 1999, Berkeley, California, United States [doi>10.1145/312624.312687]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.4 Systems and Software
      H.3.7 Digital Libraries

General Terms:
Design, Experimentation

Keywords:
collection selection, distributed information retrieval, federated search