| 1. |
- Alfalahi, Alyaa, et al.
(author)
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Expanding a dictionary of marker words for uncertainty and negation using distributional semantics
- 2015
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In: EMNLP 2015 - 6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015 : Proceedings of the Workshop - Proceedings of the Workshop. - : Association for Computational Linguistics. - 9781941643327 ; , s. 90-96
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Conference paper (peer-reviewed)abstract
- Approaches to determining the factuality of diagnoses and findings in clinical text tend to rely on dictionaries of marker words for uncertainty and negation. Here, a method for semi-automatically expanding a dictionary of marker words using distributional semantics is presented and evaluated. It is shown that ranking candidates for inclusion according to their proximity to cluster centroids of semantically similar seed words is more successful than ranking them according to proximity to each individual seed word.
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| 2. |
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| 3. |
- Argaw, Atelach Alemu, et al.
(author)
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Amharic-English information retrieval
- 2006
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In: CLEF2006 Working Notes. - : CEUR-WS.
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Conference paper (peer-reviewed)abstract
- 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.
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| 4. |
- Argaw, Atelach Alemu, et al.
(author)
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Amharic-english information retrieval
- 2007
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In: Evaluation of Multilingual and Multi-modal Information Retrieval. - 9783540749981 ; , s. 43-50
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Conference paper (peer-reviewed)abstract
- 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.
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| 5. |
- Argaw, Atelach Alemu, et al.
(author)
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Dictionary-based amharic - English information retrieval
- 2005
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In: MULTILINGUAL INFORMATION ACCESS FOR TEXT, SPEECH AND IMAGES. - BERLIN : SPRINGER-VERLAG BERLIN. - 3540274200 ; , s. 143-149
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Conference paper (peer-reviewed)abstract
- 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.
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| 6. |
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| 7. |
- Argaw, Atelach Alemu, et al.
(author)
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Dictionary-based Amharic-French information retrieval
- 2005
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In: CLEF2005 Working Notes. - : CEUR-WS.
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Conference paper (peer-reviewed)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.
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| 8. |
- Argaw, Atelach Alemu, et al.
(author)
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Dictionary-based Amharic-French information retrieval
- 2006
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In: Accessing Multilingual Information Repositories. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 354045697X ; , s. 83-92, s. 83-92
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Conference paper (peer-reviewed)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.
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| 9. |
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| 10. |
- Argaw, Atelach Alemu, 1974-
(author)
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Resource Lenient Approaches to Cross Language Information Retrieval : Using Amharic
- 2011
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Doctoral thesis (other academic/artistic)abstract
- Information Retrieval (IR) deals with finding and presenting information from a collection of documents/data that are relevant to an information need (a query) expressed by a user. Cross Language Information Retrieval (CLIR) is a subfield of IR where queries are posed in a different language than that of the document collection. Computational linguistic tools and resources are essential to accomplish the tasks in CLIR and to date, CLIR research is dominated by a very limited number of languages for which such tools and resources are available. In order to facilitate global information sharing, it is important to enable access to information using as many languages as possible. This requires an investigation into the feasibility of CLIR for languages with a limited set of computational linguistic resources. Amharic is a well-studied language with a rich history and culture, but has very limited computational linguistic tools and resources. This dissertation provides an in depth investigation into a CLIR system for Amharic (against English and French document collections). Scalable techniques were developed to accomplish Amharic CLIR tasks and each task was evaluated individually as a stand alone experiment. Large scale IR experiments were then conducted in order to evaluate the effect of three parameters, namely, transliteration, word sense discrimination, and term selection based on part of speech tags, on the overall IR performance. The effects were measured by individually tuning each of these parameters through a series of benchmarking experiments, geared towards optimizing retrieval precision as well as recall. The results give an insight into the performance of the chosen approaches, the challenges, and their impact on the overall IR performance.
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