caa a22 4500 463251431 CHVBK 20180405153341.0 cr unu---uuuuu 170326e20071201xx s 000 0 eng 10.1007/s10791-007-9033-9 doi (NATIONALLICENCE)springer-10.1007/s10791-007-9033-9 Savoy Jacques Computer Science Department, University of Neuchatel, Rue Emile Argand 11, 2009, Neuchatel, Switzerland aut Searching strategies for the Bulgarian language [Elektronische Daten] [Jacques Savoy] This paper reports on the underlying IR problems encountered when indexing and searching with the Bulgarian language. For this language we propose a general light stemmer and demonstrate that it can be quite effective, producing significantly better MAP (around + 34%) than an approach not applying stemming. We implement the GL2 model derived from the Divergence from Randomness paradigm and find its retrieval effectiveness better than other probabilistic, vector-space and language models. The resulting MAP is found to be about 50% better than the classical tf idf approach. Moreover, increasing the query size enhances the MAP by around 10% (from T to TD). In order to compare the retrieval effectiveness of our suggested stopword list and the light stemmer developed for the Bulgarian language, we conduct a set of experiments on another stopword list and also a more complex and aggressive stemmer. Results tend to indicate that there is no statistically significant difference between these variants and our suggested approach. This paper evaluates other indexing strategies such as 4-gram indexing and indexing based on the automatic decompounding of compound words. Finally, we analyze certain queries to discover why we obtained poor results, when indexing Bulgarian documents using the suggested word-based approach. Springer Science+Business Media, LLC, 2007 Cross-language information retrieval nationallicence Bulgarian IR nationallicence Stemmer nationallicence Evaluation nationallicence Morphology nationallicence Information Retrieval Springer Netherlands 10/6(2007-12-01), 509-529 1386-4564 10:6<509 2007 10 10791 https://doi.org/10.1007/s10791-007-9033-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10791-007-9033-9 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Savoy Jacques Computer Science Department, University of Neuchatel, Rue Emile Argand 11, 2009, Neuchatel, Switzerland aut NATIONALLICENCE 773 0- Information Retrieval Springer Netherlands 10/6(2007-12-01), 509-529 1386-4564 10:6<509 2007 10 10791 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer