This paper presents the statistical part-ofspeech tagger HunPoS trained on a Persian corpus. The result of the experiments shows that HunPoS provides an overall accuracy of 96.9%, which is the best result reported for Persian part-of-speech tagging.

This paper revisits ideas about the use of lattices as underlying conceptual structures in information retrieval and machine translation as suggested by researchers in the 1950s and 1960s. It describes how these ideas were originally presented, how they are related to each other and how they are represented in modern research, particularly with respect to Formal Concept Analysis.

The effect of Persian and almond gums (0, 0.1 and 0.2% (w/w)) as fat replacers and milk fat (0.4, 0.9, and 1.4% (w/w)) on physicochemical and rheological characteristics and microstructure of low-fat Iranian White cheese was studied. Persian and almond gums both effectively increased moisture-to-protein (M:P) ratio of low-fat cheese samples which in turn led to a significant reduction in the ha...

This paper reports the present results of a research on unsupervised Persian morpheme discovery. In this paper we present a method for discovering the morphemes of Persian language through automatic analysis of corpora. We utilized a Minimum Description Length (MDL) based algorithm with some improvements and applied it to Persian corpus. Our improvements include enhancing the cost function usin...

The exponential growth of the Persian blogosphere and the increased number of neologisms create a major challenge in NLP applications of Persian blogs. This paper describes a method for extracting and classifying newly constructed words and borrowings from Persian blog posts. The analysis of the occurrence of neologisms across five distinct topic categories points to a correspondence between th...

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...

Word Sense Disambiguation has long been a central problem in computational linguistics. Word Sense Disambiguation is the ability to identify the meaning of words in context in a computational manner. Statistical and supervised approaches require a large amount of labeled resources as training datasets. In contradistinction to English, the Persian language has neither any semantically tagged cor...