PEnTrans is an automatic bidirectional English/ Persian text translator. It contains two main modules, PEnT1,2. PEnT1 translates English sentences into Persian and PEnT2 performs translation from Persian to English. WSD which is an important part in translation is done in both systems by employing a combination of extended dictionary and corpus based approaches in PEnT1 and employing a combinat...

This paper presents an automated supervised method for Persian wordnet construction. Using a Persian corpus and a bi-lingual dictionary, the initial links between Persian words and Princeton WordNet synsets have been generated. These links will be discriminated later as correct or incorrect by employing seven features in a trained classification system. The whole method is just a classification...

Segmentation is a process of dividing cursive words into smaller parts in order to decrease complexity and increase accuracy of handwriting recognition process. However it is a complicated and timeconsuming task. In this paper, we introduce the concepts of basic shapes and explore its application for segmentation of Persian words. Considering a set of pre-defined shapes include line and open or...

Valency lexicons are valuable resources for natural language processing. The need for new resources for languages encourages researchers to collect new datasets. One of the most important datasets is valency lexicons. In valency lexicons, information about obligatory and optional complements of words is annotated at the syntactic and semantic levels. In this paper, we report the development of ...

WordNet is used extensively as a major lexical resource in information retrieval tasks. However, the qualities of existing Persian WordNets are far from perfect. They are either constructed manually which limits the coverage of Persian words, or automatically which results in unsatisfactory precision. This paper presents a fully-automated approach for constructing a Persian WordNet: A Bayesian ...

Finding an appropriate dataset for natural language processing applications is one of the main challenges for researches of this field. This issue is more problematic in Non-Latin languages especially Persian language. Access to an appropriate dataset that can be used in development of practical programs in language processing field, helps us to validate the obtained results and provide the fea...