Automatic Construction of Amharic Semantic Networks (ASNet)
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Date
2013-03
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Addis Ababa,University
Abstract
Semantic networks are becoming popular issues these days. Even though this popularity is
mostly related to the idea of semantic web, it is also related to the natural language applications.
Semantic networks allow search engines to search nOI only for the key words given by the user
but also for the related concepts. and show how this relation is made. Knowledge stored as
semantic networks can he used by programs that generate text from structured data. Semantic
networks are also used for document summarization by compressing the data semantically and
document classification using the knowledge stored in it. As a result, semantic networks have
become key components in many NLP applications.
In this thesis, we focused on the construction of semantic networks for Amharic text. We have
developed Amharic WordNet as initial knowledge base for the system and extracted intervening
word patterns between pairs of concepts in the WordNet for a specific relation from free text.
For each pair of concepts which we know the relationship contained in Amharic WordNet, we
search the corpus for some text snapshot between these concepts. The returned text snapshot is
processed to extract all the patterns having n·gram words between the two concepts. We have
used the WordS pace model for extraction of semantically related concepts. The process of
relation identification in among these concepts utilizes the extracted text patterns. "Part·of' and
"type·of' relations are very popular and frequently found between concepts in any corpus. We
have designed our system to extract "part·of' and "type·of' relations between concepts.
The system was tested in three different phases with different datasets from Ethiopian News
Agency and Walta Information Center. The accuracy of the system to extract pairs of concepts
having "type·of' and "part-of' relations is 68.5% and 71.7% respectively.
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Keywords
Amharic pattern extraction. Amharic relation extraction, Amharic Semantic Network, Amharic Knowledge base