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1	Distribution and Acoustic Features of Extra Linguistic Sounds in the Waxholm Corpus
	Atelach Alemu Argaw; Eva Forsbom; Ebba Gustavii
	In: http://www.speech.kth.se/~rolf/NGSLT/gslt_papers_2004/atelach-ebba-eva-termpaper.pdf (2004)
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2	An Empirical Approach to building an Amharic treebank
	Atelach Alemu; Lars Asker; Gunnar Eriksson
	In: http://w3.msi.vxu.se/~rics/TLT2003/doc/alemu_et_al.pdf (2003)
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3	GSLT: Machine Learning, Autumn 2005
	Atelach Alemu Argaw; Eva Forsbom; Teacher Joakim Nivre
	In: http://stp.ling.uu.se/~evafo/gslt/ml/ml05_atelach_eva.pdf
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4	Amharic-English Information Retrieval
	Atelach Alemu Argaw; Lars Asker
	In: http://clef.isti.cnr.it/2006/working_notes/workingnotes2006/atelachalemuargawCLEF2006.pdf
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5	An Amharic Stemmer: Reducing Words to their Citation Forms
	Atelach Alemu Argaw; Lars Asker
	In: http://acl.ldc.upenn.edu/w/w07/W07-0814.pdf
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6	Amharic-English Information Retrieval with Pseudo Relevance Feedback
	Atelach Alemu Argaw
	In: http://www.clef-campaign.org/2007/working_notes/ArgawCLEF2007.pdf
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7	Dictionary-based Amharic-French Information Retrieval
	Atelach Alemu Argaw; Lars Asker; Rickard Cöster; Jussi Karlgren; Magnus Sahlgren
	In: http://www.clef-campaign.org/2005/working_notes/workingnotes2005/argaw05.pdf
	Abstract: We present four approaches to the Amharic- French bilingual track at CLEF 2005. All experiments use a dictionary based approach to translate the Amharic queries into French Bags-of-words, but while one approach uses word sense discrimination on the translated side of the queries, the other one includes all senses of a translated word in the query for searching. We used two search engines: The SICS experimental engine and Lucene, hence four runs with the two approaches. Non-content bearing words were removed both before and after the dictionary lookup. TF/IDF values supplemented by a heuristic function was used to remove the stop words from the Amharic queries and two French stopwords lists were used to remove them from the French translations. In our experiments, we found that the SICS search engine performs better than Lucene and that using the word sense discriminated keywords produce a slightly better result than the full set of non discriminated keywords.
	Keyword: Amharic; Cross-Language Information Retrieval 1 Background; Experimentation Keywords Question answering; Languages—Query Languages General Terms Languages; Managment; Measurement; Performance
	URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.108.1749 http://www.clef-campaign.org/2005/working_notes/workingnotes2005/argaw05.pdf
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8	To appear in Information Retrieval c○Springer Verlag Classifying Amharic Webnews
	Lars Asker; Atelach Alemu; Argaw Björn Gambäck...
	In: http://www.sics.se/~gamback/publications/askerEA08.pdf
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9	2004. Dictionary-based Amharic - English Information Retrieval
	Atelach Alemu Argaw; Lars Asker; Rickard Cöster...
	In: http://www.sics.se/%7Ejussi/Artiklar/2004_CLEF_Bath/SU_SICS_CLEF04.pdf
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10	Dictionary based Amharic- English Information Retrieval
	Atelach Alemu Argaw; Lars Asker; Jussi Karlgren
	In: http://www.sics.se/~jussi/Artiklar/2004_CLEF_Bath/arkiv/report2 Folder/clef_aack.pdf
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11	Dictionary based Amharic- English Information Retrieval
	Atelach Alemu Argaw; Lars Asker; Jussi Karlgren
	In: http://www.sics.se/~jussi/Artiklar/2004_CLEF_Bath/arkiv/aack/clef_aack.pdf
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