Abstract
For our first participation in CLEF we chose the domain specific GIRT corpus. We implemented the adaptive fusion model MIMOR (Multiple Indexing and Method-Object Relations) which is based on relevance feedback. The linear combination of several retrieval engines was optimized. As a basic retrieval engine, IRF from NIST was employed. The results are promising. For several topics, our runs achieved a performance above the average. The optimization based on topics and relevance judgements from CLEF 2001 proved to be a fruitful strategy.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mandl, T., Womser-Hacker, C.: Probability Based Clustering for Document and User Properties. In: Ojala, T. (ed.): Infotech Oulo International Workshop on Information Retrieval (IR 2001). Oulo, Finland. Sept 19–21 2001. 100-107
Womser-Hacker, C.: Das MIMOR-Modell. Mehrfachindexierung zur dynamischen Methoden-Objekt-Relationierung im Information Retrieval. Habilitationsschrift. Universität Regensburg, Informationswissenschaft (1997)
McCabe, M., Chowdhury, A., Grossmann, D., Frieder, O.: A Unified Framework for Fusion of Information Retrieval Approaches. In: Eigth ACM Conference on Information and Knowledge Management (CIKM) ACM Press, New York, NY, USA (1999) 330–334
Mandl, T., Womser-Hacker, C.: Fusion Approaches for Mappings Between Heterogeneous Ontologies. In: Constantopoulos, Panos; Sølvberg, Ingeborg (eds.): Research and Advanced Technology for Digital Libraries: 5th European Conference (ECDL) Lecture Notes in Computer Science, Vol. 2163 Springer-Verlag, Berlin Heidelberg New York (2001) 83–94
Vogt, C., Cottrell, G.: Predicting the Performance of Linearly Combined IR Systems. In: 21th Annual Intl ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)) ACM Press, New York, NY, USA (1998) 190–196
Drucker, H., Wu, D., Vapnik, V.: Support Vector Machines for Spam Categorization. IEEE Trans. on Neural Networks 10 (1999) 1048–1054
Joachims, T.: Text Categorization with Support Vector Machines: Learning with Many Relevant Features. In: European Conference on Machine Learning (ECML 1998) 137-142
Iyer, R., Lewis, D., Schapire, R., Singer, Y., Singhal, A.: Boosting for Document Routing. In: Ninth ACM Conference on Information and Knowledge Management (CIKM) ACM Press, New York, NY, USA (2000) 70–77
Kluck, M., Gey, F.: The Domain-Specific Task of CLEF — Specific Evaluation Strategies in Cross-Language Information Retrieval. In: Peters, Carol (ed.): Cross-Language Information Retrieval and Evaluation. Workshop of the Cross-Language Information Evaluation Forum (CLEF) Lecture Notes in Computer Science, Vol. 2069 Springer-Verlag, Berlin Heidelberg New York (2000) 48–56
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hackl, R., Kölle, R., Mandl, T., Womser-Hacker, C. (2003). Domain Specific Retrieval Experiments with MIMOR at the University of Hildesheim. In: Peters, C., Braschler, M., Gonzalo, J., Kluck, M. (eds) Advances in Cross-Language Information Retrieval. CLEF 2002. Lecture Notes in Computer Science, vol 2785. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45237-9_30
Download citation
DOI: https://doi.org/10.1007/978-3-540-45237-9_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40830-7
Online ISBN: 978-3-540-45237-9
eBook Packages: Springer Book Archive