Natural language processing (NLP) has recently gained much attention for representing and
analyzing human language computationally. It has spread its applications in various fields …

The analysis of sentiment in text has mainly been focused on the English language. The
complexity of the Arabic language and its linguistic features that oppose those found in …

The focus of data scientists is essentially divided into three areas: collecting data, analyzing
data, and inferring information from data. Each one of these tasks requires special …

Abstract Part-of-speech (POS) tagging is one of the most important addressed areas in the
natural language processing (NLP). There are effective POS taggers for many languages …

Parts of Speech (POS) tagging is one of the most well-studied problems in the field of
Natural Language Processing (NLP). In this paper, a Neural Network Language Models …

Lemmatization—computing the canonical forms of words in running text—is an important
component in any NLP system and a key preprocessing step for most applications that rely …

Arabic is an old Semitic language, the standardization of its lexicon and grammar are deeply
rooted and well established a long time ago in history. Arabic is a morphologically rich …

Recently, more data-driven approaches are demanding multilingual parallel resources
primarily in the cross-language studies. To meet these demands, building multilingual …

Analyzing product online reviews has drawn much interest in the academic field. In this
research, a new probabilistic topic model, called tag sentiment aspect models (TSA), is …

Over the years, many different algorithms are proposed to improve the accuracy of the
automatic parts of speech tagging. High accuracy of parts of speech tagging is very …