Automated classification of text into predefined categories has always been considered as a
vital method to manage and process a vast amount of documents in digital forms that are …

Document classification is a classical problem in information retrieval, and plays an
important role in a variety of applications. Automatic document classification can be defined …

Recent research on Big Data proposed and evaluated a number of advanced techniques to
gain meaningful information from the complex and large volume of data available on the …

Text categorization or classification (TC) is concerned with placing text documents in their
proper category according to their contents. Owing to the various applications of TC and the …

In this paper, we propose to build a morpho-semantic knowledge graph from Arabic
vocalized corpora. Our work focuses on classical Arabic as it has not been deeply …

Document Classification (DC) is one of the fundamental problems in text mining. Plenty of
works exist on DC with interesting approaches and excellent results, however, most of them …

Question answering system aims at retrieving precise information from a large collection of
documents. This work presents a question answering method to apply on Hadith in order to …

Stemming is one of the basic steps in natural language processing applications such as
information retrieval, parts of speech tagging, syntactic parsing and machine translation, etc …

Objectives: Information overload on the web is a major problem faced by institutions and
businesses today. Sorting out some useful documents from the web which is written in …

The information retrieval is the task of obtaining relevant information from a large collection
of databases. Preprocessing plays an important role in information retrieval to extract the …