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  • 1.
    Argaw, Atelach Alemu
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Amharic-English information retrieval with pseudo relevance feedback2007In: CLEF2007 Working Notes, CEUR-WS , 2007Conference paper (Refereed)
    Abstract [en]

    We describe cross language retrieval experiments using Amharic queries and English language document collection from our participation in the bilingual ad hoc track at the CLEF 2007. Two monolingual and eight bilingual runs were submitted. The bilingual experiments designed varied in terms of usage of long and short queries, presence of pseudo relevance feedback (PRF), and three approaches (maximal expansion, first-translation-given, manual) for word sense disambiguation. We used an Amharic-English machine readable dictionary (MRD) and an online Amharic-English dictionary in order to do the lookup translation of query terms. In utilizing both resources, matching query term bigrams were always given precedence over unigrams. Out of dictionary Amharic query terms were taken to be possible named entities in the language, and further filtering was attained through restricted fuzzy matching based on edit distance. The fuzzy matching was performed for each of these terms against automatically extracted English proper names. The Lemur toolkit for language modeling and information retrieval was used for indexing and retrieval. Although the experiments are too limited to draw conclusions from, the obtained results indicate that longer queries tend to perform similar to short ones, PRF improves performance considerably, and that queries tend to fare better when we use the first translation given in the MRD rather than using maximal expansion of terms by taking all the translations given in the MRD.

  • 2.
    Argaw, Atelach Alemu
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Amharic-English Information Retrieval with Pseudo Relevance Feedback2008In: Advances In Multilingual And Multimodal Information Retrieval / [ed] Peters, C; Jikoun, V; Mandl, T; Muller, H; Oard, DW; Penas, A; Petras, V; Santos, D, 2008, Vol. 5152, p. 119-126Conference paper (Refereed)
    Abstract [en]

    We describe cross language retrieval experiments using Amharic queries and English language d ocument collection. Two monolingual and eight bilingual runs were submitted with variations in terms of 1 sage of long and short queries, presence of pseudo relevance feedback (PRF), and approaches for word sense disambiguation (WSD). We used an Amharic-English machine readable dictionary (MRD), and an online Amharic-English dictionary for lookup translation of query terms. Out of dictionary Amharic query terms were considered as possible named entities, and further filtering was attained through restricted fuzzy matching based on edit distance which is calculated against automatically extracted English proper names. The obtained results indicate that longer queries tend to perform similar to short ones, PRF improves performance considerably, and that queries tend to fare better with WSD rather than using maximal expansion of terms by taking all the translations given in the MRD.

  • 3.
    Argaw, Atelach Alemu
    et al.
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Asker, Lars
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Amharic-English information retrieval2006In: CLEF2006 Working Notes, CEUR-WS , 2006Conference paper (Refereed)
    Abstract [en]

    We describe Amharic-English cross lingual information retrieval experiments in the adhoc bilingual tracs of the CLEF 2006. The query analysis is supported by morphological analysis and part of speech tagging while we used different machine readable dictionaries for term lookup in the translation process. Out of dictionary terms were handled using fuzzy matching and Lucene[4] was used for indexing and searching. Four experiments that differed in terms of utilized fields in the topic set, fuzzy matching, and term weighting, were conducted. The results obtained are reported and discussed.

  • 4.
    Argaw, Atelach Alemu
    et al.
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Asker, Lars
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Amharic-english information retrieval2007In: Evaluation of Multilingual and Multi-modal Information Retrieval / [ed] Peters, C, 2007, Vol. 4730, p. 43-50Conference paper (Refereed)
    Abstract [en]

    We describe Amharic-English cross lingual information retrieval experiments in the ad hoc bilingual tracks of the CLEF 2006. The query analysis is supported by morphological analysis and part of speech tagging while we used two machine readable dictionaries supplemented by online dictionaries for term lookup in the translation process. Out of dictionary terms were handled using fuzzy matching and Lucene[4] was used for indexing and searching. Four experiments that differed in terms of utilized fields in the topic set, fuzzy matching, and term weighting, were conducted. The results obtained are reported and discussed.

  • 5.
    Argaw, Atelach Alemu
    et al.
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Asker, Lars
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Coster, R
    Karlgren, J
    Dictionary-based amharic - English information retrieval2005In: MULTILINGUAL INFORMATION ACCESS FOR TEXT, SPEECH AND IMAGES / [ed] Peters, C; Clough, P; Gonzalo, J; Jones, GJF; Kluck, M; Magnini, B, BERLIN: SPRINGER-VERLAG BERLIN , 2005, Vol. 3491, p. 143-149Conference paper (Refereed)
    Abstract [en]

    We present two approaches to the Amharic - English bilingual track in CLEF 2004. Both experiments use a dictionary based approach to translate the Amharic queries into English Bags-of-words, but while one approach removes non-content bearing words from the Amharic queries based on their IDF value, the other uses a list of English stop words to perform the same task. The resulting translated (English) terms are then submitted to a retrieval engine that supports the Boolean and vector-space models. In our experiments, the second approach (based on a list of English stop words) performs slightly better than the one based on IDF values for the Amharic terms.

  • 6.
    Argaw, Atelach Alemu
    et al.
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Asker, Lars
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Coster, Rickard
    Karlgren, Jussi
    Sahlgren, Magnus
    Dictionary-based Amharic-French information retrieval2006In: Accessing Multilingual Information Repositories / [ed] Peters, C; Gey, FC; Gonzalo, J; Muller, H; Jones, GJF; Kluck, M; Magnini, B; DeRijke, M, 2006, Vol. 4022, p. 83-92Conference paper (Refereed)
    Abstract [en]

    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.

  • 7.
    Argaw, Atelach Alemu
    et al.
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Asker, Lars
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Karlgren, J.
    Sahlgren, M.
    Cöster, R.
    Dictionary-based Amharic-French information retrieval2005In: CLEF2005 Working Notes, CEUR-WS , 2005Conference paper (Refereed)
    Abstract [en]

    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.

1 - 7 of 7
CiteExportLink to result list
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  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
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