Semi-supervised approach for Persian word sense disambiguation

Word-sense disambiguation is one of the key concepts in natural language processing. The main goal of a language is to present a specific concept to the audience. This concept is extracted from the meaning of words in that language. System should be able to identify role and meaning of words in order to identify the concepts in texts properly. This issue becomes more problematic if there are words that take different meanings because of their surrounding words. Regarding that different practical programs have been developed in Persian language, it is vital now to find a solution for word-sense disambiguation in Persian language. Lack of training data is the biggest challenge in the course of word-sense disambiguation in Persian language. In order to face this problem, machine learning approach with minimal supervision is employed in this research. The applied method tries to disambiguate word senses by considering defined features of target words and applying collaborative learning method. Extracted corpus from published news by news agencies is used as the reference corpus. Evaluating the program by the available corpus on three considered ambiguous words, the implemented method has been able to properly identify the meaning of 5368 documents with 88% recall, 95% precision and 93% accuracy rate.

I. Introduction

Word-sense disambiguation means to determine the right meaning of a word which is ambiguous at the first sight and it seems to have several semantic classes. Generally, words with more than a single meaning can be set as target words and our aim is to disambiguate their sense. Humans can easily identify the right meaning of a word based on deduced concept from the sentence, but computer needs more information than only the input sentence in order to identify semantic class of an ambiguous word. By applying disambiguation methods it is possible to extract concepts of a sentence and give it to computer to decide about semantic class of ambiguous word. Word-sense disambiguation is highly taken into consideration in prevalent languages like English and lots of research has been carried out in order to disambiguate words in English language.