Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
ACM SIGIR Forum
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Information retrieval
Using statistical testing in the evaluation of retrieval experiments
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
An algorithm for suffix stripping
Readings in information retrieval
Overview of the sixth text REtrieval conference (TREC-6)
Information Processing and Management: an International Journal - The sixth text REtrieval conference (TREC-6)
Viewing morphology as an inference process
Artificial Intelligence - Special issue on Intelligent internet systems
European Research Letter: cross-language system evaluation: the CLEF campaigns
Journal of the American Society for Information Science and Technology
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
The Effectiveness of a Graph-Based Algorithm for Stemming
ICADL '02 Proceedings of the 5th International Conference on Asian Digital Libraries: Digital Libraries: People, Knowledge, and Technology
Unsupervised learning of the morphology of a natural language
Computational Linguistics
Handbook of Parametric and Nonparametric Statistical Procedures
Handbook of Parametric and Nonparametric Statistical Procedures
Stemming and decompounding for German text retrieval
ECIR'03 Proceedings of the 25th European conference on IR research
YASS: Yet another suffix stripper
ACM Transactions on Information Systems (TOIS)
Improvement of building field association term dictionary using passage retrieval
Information Processing and Management: an International Journal
Restricted inflectional form generation in management of morphological keyword variation
Information Retrieval
Qualitative geocoding of persistent web pages
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
HITS Can Converge Slowly, but Not Too Slowly, in Score and Rank
COCOON '09 Proceedings of the 15th Annual International Conference on Computing and Combinatorics
Providing Universal Access to History Textbooks: A Modified GIS Case
W2GIS '09 Proceedings of the 9th International Symposium on Web and Wireless Geographical Information Systems
New approach for field association term dictionary with passage retrieval
ACMOS'07 Proceedings of the 9th WSEAS international conference on Automatic control, modelling and simulation
A novel corpus-based stemming algorithm using co-occurrence statistics
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Research on Language and Computation
GRAS: An effective and efficient stemming algorithm for information retrieval
ACM Transactions on Information Systems (TOIS)
A system architecture as a support to a flexible annotation service
DELOS'04 Proceedings of the 6th Thematic conference on Peer-to-Peer, Grid, and Service-Orientation in Digital Library Architectures
Translation techniques in cross-language information retrieval
ACM Computing Surveys (CSUR)
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
Effective and Robust Query-Based Stemming
ACM Transactions on Information Systems (TOIS)
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In this paper we will present a language-independent probabilistic model which can automatically generate stemmers. Stemmers can improve the retrieval effectiveness of information retrieval systems, however the designing and the implementation of stemmers requires a laborious amount of effort due to the fact that documents and queries are often written or spoken in several different languages. The probabilistic model proposed in this paper aims at the development of stemmers used for several languages. The proposed model describes the mutual reinforcement relationship between stems and derivations and then provides a probabilistic interpretation. A series of experiments shows that the stemmers generated by the probabilistic model are as effective as the ones based on linguistic knowledge.