Abstract
Information Retrieval Systeme haben in den letzten Jahren nur geringe Verbesserungen in der Retrieval Performance erzielt. Wir arbeiten an neuen Ansätzen, dem sogenannten Collaborativen Information Retrieval (CIR), die das Potential haben, starke Verbesserungen zu erreichen. CIR ist die Methode, mit der durch Ausnutzen von Informationen aus früheren Anfragen die Retrieval Peformance für die aktuelle Anfrage verbessert wird. Wir haben ein eingeschränktes Szenario, in dem nur alte Anfragen und dazu relevante Antwortdokumente zur Verfügung stehen. Neue Ansätze für Methoden der Query Expansion führen unter diesen Bedingungen zu Verbesserungen der Retrieval Performance .
Abstract
The accuracy of ad-hoc document retrieval systems has reached a stable plateau in the last few years. We are working on so-called collaborative information retrieval (CIR) systems which have the potential to overcome the current limits. We define CIR as a task, where an information retrieval (IR) system uses information gathered from previous search processes from one or several users to improve retrieval performance for the current user searching for information. We focus on a restricted setting in CIR in which only old queries and correct answer documents to these queries are available for improving a new query. For this restricted setting we propose new approaches for query expansion procedures. We show how CIR methods can improve overall IR performance.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Literatur
Agichtein E, Lawrence S, Gravano L (2001) Learning search engine specific query transformations for question answering. Proceedings of the 10th International World Wide Web Conference, pp 169–178
Baeza-Yates R, Ribeiro-Neto B (1999) Modern Information Retrieval. Addison-Wesley Publishing Company
Buckley C, Salton G, Allan J, Singhal A (1994) Automatic query expansion using smart. NIST Special Publication 500-226: Proceedings of the Third Text Retrieval Conference (TREC-3), pp 69–80
Crestani F, van Rijsbergen CJ (1998) A study of probability kinematics in information retrieval. ACM Transactions on Information Systems (TOIS) 16(3):225–255
Cui H, Wen J-R, Nieand J-Y, Ma W-Y (2002) Probabilistic query expansion using query logs. Eleventh International World Wide Web Conference
Dominich S (2001) Relevance Effectiveness in Information Retrieval, chapter 5. Mathematical Foundations of Information Retrieval. Kluwer Academic Publishers, pp 215–232
Efthimiadis EN (1996) Query expansion. Annual Review of Information Science and Technology 31:121–187
Fuhr N, Buckley C (1991) A Probabilistic Learning Approach for Document Indexing. ACM Transactions on Information Systems 9(3):223–248
Fuhr N (1996) Goals and tasks of the IR group. Homepage of the IR group of the German Informatics Society. http://ls6-www.cs.uni-dortmund.de/ir/fgir/ mitgliedschaft/brochure2.html
Harman D (1992) Relevance feedback revisited. Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 1–10
Henrich A (2002) IR research at university of bayreuth. Homepage of the IR-research group. http://ai1.inf.uni-bayreuth.de/forschung/ forschungsgebiete/ir_mmdb
Hull D (1993) Using statistical testing in the evaluation of retrieval experiments. 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 329–338
Hust A, Junker M, Dengel A (2004) A Mathematical Model for Improving Retrieval Performance in Collaborative Information Retrieval. Kluwer Information Retrieval Special Issue: Advances in Mathematical/Formal Methods in Information Retrieval. To appear
Hust A, Klink S, Junker M, Dengel A (2002) Query Expansion for Web Information Retrieval. Proceedings of Web Information Retrieval Workshop, 32nd Annual Conference of the German Informatics Society, Lecture Notes in Informatics, vol P-19, pp 176–180
Hust A, Klink S, Junker M, Dengel A (2002) Query Reformulation in Collaborative Information Retrieval. Proceedings of the International Conference on Information and Knowledge Sharing, IKS 2002, pp 95–100
Joachims T (2002) Unbiased evaluation of retrieval quality using clickthrough data. Technical report, Cornell University, Department of Computer Science
Kise K, Junker M, Dengel A, Matsumoto K (2001) Experimental evaluation of passage-based document retrieval. Sixth International Conference on Document Analysis and Recognition ICDAR-01, pp 592–596
Kolda TG, O’Leary DP (1998) A semidiscrete matrix decomposition for latent semantic indexing information retrieval. ACM Transactions on Information Systems 16(4):322–346
Manning CD, Schütze H (1999) Foundations of Natural Language Processing. MIT Press
Minker J, Wilson G, Zimmerman B (1972) An evaluation of query expansion by the addition of clustered terms for a document retrieval system. Information Storage and Retrieval 8:329–348
Phibot search engine (2002) Homepage. http://phibot.org
Qiu Y, Frei H-P (1993) Concept-based query expansion. Proceedings of the 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 160–169
Raghavan VV, Sever H (1995) On the reuse of past optimal queries. 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 344–350
Salton G (1971) The SMART retrieval system – experiments in automatic document processing. Prentice Hall, Englewood Cliffs, New Jersey
Salton G, Buckley C (1988) Term weighting approaches in automatic text retrieval. Information Processing & Management 24(5):513–523
Salton G, McGill MJ (1983) Introduction to Modern Information Retrieval. McGraw-Hill Book Co., New York
Sever H (1995) Knowledge Structuring for Database Mining and Text Retrieval Using Past Optimal Queries. PhD thesis, University of Louisiana, Lafayette, LA
Ftp directory at cornell university (1968–1988) Homepage. ftp://ftp.cs.cornell.edu/pub/smart
Sparck-Jones K, Needham RM (1968) Automatic term classification and retrieval. Information Storage and Retrieval 4:91–100
Text REtrieval Conference (TREC) (1992–2003) Homepage. http://trec.nist.gov
van Rijsbergen CJ (1979) Information Retrieval. Butterworths, London
van Rijsbergen CJ (1989) Towards an information logic. Proceedings of the 12th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 77–86
von Neumann J, Morgenstern O (1944) Theory of Games and Economic Behavior. Princeton University Press
Wen J-R, Nie J-Y, Zhang H-J (2002) Query clustering using user logs. ACM Transactions on Information Systems 20(1):59–81
White RW, Ruthven I, Jose JM (2002) The use of implicit evidence for relevance feedback in web retrieval. Advances in Information Retrieval, 24th BCS-IRSG European Colloquium on IR Research, ECIR 2002, Proceedings, Lecture Notes in Computer Science, vol 2291, pp 93–109
Xu J, Croft WB (2000) Improving the effectiveness of information retrieval with local context analysis. ACM Transactions on Information Systems 18(1):79–112
Author information
Authors and Affiliations
Additional information
CR Subject Classification
H.3.3
Rights and permissions
About this article
Cite this article
Hust, A. Query expansion methods for collaborative information retrieval. Informatik Forsch. Entw. 19, 224–238 (2005). https://doi.org/10.1007/s00450-004-0174-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00450-004-0174-4