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Published in:
2011 | OriginalPaper | Chapter
A Semi-supervised Approach for Key-Synset Extraction to Be Used in Word Sense Disambiguation
Authors : Maryam Haghollahi, Mehrnoush Shamsfard
Published in: Information Retrieval Technology
Publisher: Springer Berlin Heidelberg
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Nowadays, although many researches is being done in the field of word sense disambiguation in some languages like English, still some other languages like Persian have many things to be done. Some difficulties are in this way which might have made it less interactive for researchers. For example, Persian WordNet or FarsNet is newly developed and there is no sense tagged corpus developed based on it yet. So we propose a semi-supervised approach for extending FarsNet with some new relations and then use it for WSD. Also a method to extract semantic keywords or key-concepts from textual documents is used. As the key-concepts are extracted exploiting FarsNet, we call them Key-synsets. In fact Key-synsets of a document are those synsets which are semantically related to the main subjects of that document. This method is exploited to improve the precision of the proposed WSD. Although our approach is tested on Persian it can be easily adopted for other languages such as English.