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To appear in Information Retrieval c○Springer Verlag Classifying Amharic Webnews
Lars Asker
;
Atelach Alemu
;
Argaw Björn Gambäck
;
Samuel Eyassu
;
Asfeha Lemma
;
Nigussie Habte
;
B. Gambäck (b
In: http://www.sics.se/~gamback/publications/askerEA08.pdf
Abstract:
Abstract We present work aimed at compiling an Amharic corpus from the Web and automatically categorizing the texts. Amharic is the second most spoken Semitic language in the World (after Arabic) and used for countrywide communication in Ethiopia. It is highly inflectional and quite dialectally diversified. We discuss the issues of compiling and annotating a corpus of Amharic news articles from the Web. This corpus was then used in three sets of text classification experiments. Working with a less-researched language highlights a number of practical issues that might otherwise receive less attention or go unnoticed. The purpose of the experiments has not primarily been to develop a cutting-edge text classification system for Amharic, but rather to put the spotlight on some of these issues. The first two sets of experiments investigated the use of Self-Organizing Maps (SOMs) for document classification. Testing on small datasets, we first looked at classifying unseen data into ten predefined categories of news items, and then at clustering it around query content, when taking sixteen queries as class labels. The second set of experiments investigated the effect of operations such as stemming and part-of-speech tagging on text classification performance. We compared three representations while constructing classification models
Keyword:
Department of Computer and Systems Sciences
;
Stockholm
;
Stockholm University
;
Sweden
URL:
http://www.sics.se/~gamback/publications/askerEA08.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.5234
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