Amsalu, SabaLisanu, KiburHailemeskel, Tewodros2018-11-302023-11-182018-11-302023-11-182003-07http://etd.aau.edu.et/handle/12345678/14764The increase in the amount of electronic information has caused increasing need for efficient information retrieval techniques. Most techniques to retrieving textual materials from databases depend on exact term match between terms in user’s query and terms by which documents are indexed. However, since there are usually many ways to express the same concept, the terms in the user’s query may not appear in a relevant document. Alternatively, many words can have more than one meaning. Due to these facts term matching methods are likely to miss relevant documents and also retrieve irrelevant ones (Dumais, 1992; Berry, Dumais & Letsche, 1995). The Latent Semantic Indexing (LSI) technique of information retrieval can partially handle these problems by organizing terms and documents into a “semantic” structure more appropriate for information retrieval. This is done by modeling the inherent higher-order pattern in the association of terms with documents. In this thesis, the potential of LSI approach in Amharic text retrieval is investigated. 206 Amharic documents and 25 queries were used to test the approach. Automatic indexing of the documents resulted in 9256 unique terms which are not in the stop-word list used for the research. A 110-factor SVD of the term by document matrix is used for indexing and retrieval. Finally, the performance of the LSI approach is compared with the standard vector space. Except at one standard recall level (0.80) precision of the LSI approach was above that of the standard vector space.enText RetrievalThesis