Statistical inference in retrieval effectiveness evaluation
Information Processing and Management: an International Journal
Experimentation as a way of life: Okapi at TREC
Information Processing and Management: an International Journal - The sixth text REtrieval conference (TREC-6)
Probabilistic models of information retrieval based on measuring the divergence from randomness
ACM Transactions on Information Systems (TOIS)
Combining Multiple Strategies for Effective Monolingual and Cross-Language Retrieval
Information Retrieval
How Effective is Stemming and Decompounding for German Text Retrieval?
Information Retrieval
Comparative study of monolingual and multilingual search models for use with asian languages
ACM Transactions on Asian Language Information Processing (TALIP)
Searching strategies for the Hungarian language
Information Processing and Management: an International Journal
Searching in Medline: Query expansion and manual indexing evaluation
Information Processing and Management: an International Journal
Addressing morphological variation in alphabetic languages
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Algorithmic stemmers or morphological analysis? An evaluation
Journal of the American Society for Information Science and Technology
Indexing and stemming approaches for the Czech language
Information Processing and Management: an International Journal
Indexing and searching strategies for the Russian language
Journal of the American Society for Information Science and Technology
CLEF 2009 ad hoc track overview: TEL and Persian tasks
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
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This paper describes our participation to the Persian ad hoc search during the CLEF 2009 evaluation campaign. In this task, we suggest using a light suffix-stripping algorithm for the Farsi (or Persian) language. The evaluations based on different probabilistic models demonstrated that our stemming approach performs better than a stemmer removing only the plural suffixes, or statistically better than an approach ignoring the stemming stage (around +4.5%) or a n-gram approach (around +4.7%). The use of a blind query expansion may significantly improve the retrieval effectiveness (between +7% to +11%). Combining different indexing and search strategies may further enhance the MAP (around +4.4%).