Ahmed, F.; Nürnberger, A.: Evaluation of n-gram conflation approaches for Arabic text retrieval (2009)
0.00
0.0044962796 = product of:
0.031473957 = sum of:
0.0060537956 = weight(_text_:information in 2941) [ClassicSimilarity], result of:
0.0060537956 = score(doc=2941,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.116372846 = fieldWeight in 2941, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=2941)
0.025420163 = weight(_text_:retrieval in 2941) [ClassicSimilarity], result of:
0.025420163 = score(doc=2941,freq=4.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.2835858 = fieldWeight in 2941, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=2941)
0.14285715 = coord(2/14)
- Abstract
- In this paper we present a language-independent approach for conflation that does not depend on predefined rules or prior knowledge of the target language. The proposed unsupervised method is based on an enhancement of the pure n-gram model that can group related words based on various string-similarity measures, while restricting the search to specific locations of the target word by taking into account the order of n-grams. We show that the method is effective to achieve high score similarities for all word-form variations and reduces the ambiguity, i.e., obtains a higher precision and recall, compared to pure n-gram-based approaches for English, Portuguese, and Arabic. The proposed method is especially suited for conflation approaches in Arabic, since Arabic is a highly inflectional language. Therefore, we present in addition an adaptive user interface for Arabic text retrieval called araSearch. araSearch serves as a metasearch interface to existing search engines. The system is able to extend a query using the proposed conflation approach such that additional results for relevant subwords can be found automatically.
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.7, S.1448-1465
