A STATISTICAL MODEL TO ENHANCE TOPIC DETECTION OF ARABIC TEXT

the innovation of a statistical model to estimate dependable rainfall (dr) and develop it for determination and classification of drought and wet years of iran

آب حاصل از بارش منبع تأمین نیازهای بی شمار جانداران به ویژه انسان است و هرگونه کاهش در کم و کیف آن مستقیماً حیات موجودات زنده را تحت تأثیر منفی قرار می دهد. نوسان سال به سال بارش از ویژگی های اساسی و بسیار مهم بارش های سالانه ایران محسوب می شود که آثار زیان بار آن در تمام عرصه های اقتصادی، اجتماعی و حتی سیاسی- امنیتی به نحوی منعکس می شود. چون میزان آب ناشی از بارش یکی از مولفه های اصلی برنامه ...

Statistical denormalization for Arabic text

In this paper, we focus on a sub-problem of Arabic text error correction, namely Arabic Text Denormalization. Text Denormalization is considered an important post-processing step when performing machine translation into Arabic. We examine different approaches for denormalization via the use of language modeling, stemming, and sequence labeling. We show the effectiveness of different approaches ...

Experiments with Arabic Topic Detection

The continuous growth of information on the Internet and the availability of a large mass of electronic documents in Arabic language make Natural Language processing (NLP) tasks play an important role to enhance and facilitate the access and the exploitation of information. Among available NLP tasks, we are interested in Arabic Topic Detection. Our objective is to realize an indexing system cap...

A New Model for Text Coherence Evaluation using Statistical Characteristics

Using Statistical Properties to Enhance Text Categorization

Statistical properties extracted from text are useful in many areas. Knowing who authored some text or knowing the category of a text is among the uses of collecting such statistics. In this paper, language-independent properties of text are studied using two categorized corpora of news articles. It is observed that the properties do not depend on the corpus nor on its size. Several interesting...