One of the common processes in the field of text mining is text classification.Because of the complex nature of Farsi language, words with separate parts and combined verbs, the most of text classification systems are not applicable to Farsi texts.K-Nearest Neighbors (KNN) is one of the most popular used methods for text classification and presents good performance in experiments on different d...

The present study aims at the description and analysis of the phonological and lexical development of a child who is acquiring Farsi as his first language. The child's language production at the holophrastic stage of language development, mainly single words, is observed and recorded  longitudinally for nearly seven  months since he was 16 months old until he turned 23 months. An attempt is mad...

In this paper, we address the shortage of evaluation benchmarks on Persian (Farsi) language by creating and making available a new benchmark for English to Persian Cross Lingual Word Sense Disambiguation (CL-WSD). In creating the benchmark, we follow the format of the SemEval 2013 CL-WSD task, such that the introduced tools of the task can also be applied on the benchmark. In fact, the new benc...

Cognates are words in different languages that are associated with each other by language learners. Thus, cognates are important indicators for the prediction of the perceived difficulty of a text. We introduce a method for automatic cognate production using character-based machine translation. We show that our approach is able to learn production patterns from noisy training data and that it w...

Determining the language proficiency level required to understand a given text is a key requirement in vetting documents for use in second language learning. In this work, we describe our approach for developing an automatic text analytic to estimate the text difficulty level using the Interagency Language Roundtable (ILR) proficiency scale. The approach we take is to use machine translation to...

There are several methods offered for spelling correction in Farsi (Persian) Language. Unfortunately no powerful framework has been implemented because of lack of a large training set in Farsi as an accurate model. A training set consisting of erroneous and related correction string pairs have been obtained from a large number of instances of the books each of which were typed two times in Comp...

Nowadays, OCR systems have got several applications and are increasingly employed in daily life. Much research has been done regarding the identification of Latin, Japanese, and Chinese characters. However, very little investigation has been performed regarding Farsi/Arabic characters recognition. Probably the reason is difficulty and complexity of those characters identification compared to th...

Named Entity Recognition is a main task in the NLP area that has yielded multiple web-based natural language processors gaining popularity in the Semantic Web community for extracting knowledge from web data. These processors are generally located as pipelines, using dedicated APIs and various taxonomy for extracting, classifying and disambiguating named entities. In this paper, we address the ...