2015 First International Conference on Arabic Computational Linguistics (ACLing)

17-20 April 2015

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  • [Front cover]

    Publication Year: 2015, Page(s): C4
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  • [Title page i]

    Publication Year: 2015, Page(s): i
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  • [Title page iii]

    Publication Year: 2015, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2015, Page(s): iv
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  • Table of contents

    Publication Year: 2015, Page(s):v - vii
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  • Preface

    Publication Year: 2015, Page(s): viii
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  • Conference Organization

    Publication Year: 2015, Page(s):ix - xii
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  • Tunisian Arabic aeb Wordnet: Current State and Future Extensions

    Publication Year: 2015, Page(s):3 - 8
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (539 KB) | HTML iconHTML

    Nowadays, Internet communication and especially informal Internet communication such as social networks, blogs, etc. is directing politic, economic, financial and social environments all over the world. Consequently, Internet monitoring is taking more and more scale particularly in Tunisia suffering from unsteadiness since the politic revolution in 2011. In a Tunisian context, Internet communicati... View full abstract»

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  • Unsupervised Data Driven Taxonomy Learning

    Publication Year: 2015, Page(s):9 - 14
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (275 KB) | HTML iconHTML

    The ability to effectively organize textual information is a big challenge in intelligent text processing. With the increase in the amount of textual data being generated, this task is becoming more and more essential. In this paper we present an unsupervised computer-aided tool for automatically building classification schemes and taxonomies for enhancing the process of automated text classificat... View full abstract»

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  • Enrichment of the Arabic Treebank ATB with Syntactic Properties

    Publication Year: 2015, Page(s):15 - 20
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (208 KB) | HTML iconHTML

    The enrichment of Arabic treebank with syntactic properties provides the increase of its use in different applications, the acquisition of new linguistic resources and the alleviation of the probabilistic parsing process by using statistics to limit the properties to satisfied ones. This method of enrichment requires two steps to follow starting by inducting a Property Grammar from a source treeba... View full abstract»

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  • Building a Corpus for Arabic Dialects Using Games with a Purpose

    Publication Year: 2015, Page(s):21 - 25
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (185 KB) | HTML iconHTML

    There is a huge gap between the written form of Arabic, Modern Standard Arabic (MSA), and the different spoken Arabic dialects due to the big number of dialects. In addition, most Arabic data-sets are formed for MSA content. Traditional ways of identifying dialects of texts are time and money consuming. In addition, due to the morphological complexity of Arabic, the gender of the speaker may chang... View full abstract»

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  • Arabic Natural Language Processing from Software Engineering to Complex Pipeline

    Publication Year: 2015, Page(s):29 - 36
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (301 KB)

    Arabic Natural Language Processing (ANLP) has known an important development during the last decade. Nowadays, Several ANLP tools are developed such as morphological analyzers, syntactic parsers, etc. These tools are characterized by their diversity in terms of development languages used, inputs/outputs manipulated, internal and external representations of results, etc. This is mainly due to the l... View full abstract»

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  • Toward the Resolution of Arabic Lexical Ambiguities with Transduction on Text Automaton

    Publication Year: 2015, Page(s):37 - 42
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (188 KB)

    Lexical analysis can be a way to remove ambiguities in Arabic language. So their resolution is an important task in several Natural Language Processing (NLP) applications. In this context that this paper is inscribed. Our proposed resolution method is based essentially on the use of transducers on text automata. Indeed these transducers specify the lexical and contextual rules for Arabic language.... View full abstract»

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  • A Proposed Approach for Arabic Language Segmentation

    Publication Year: 2015, Page(s):43 - 48
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (177 KB)

    This paper presents a research about natural language processing (NLP). Our area of interest is the process of Arabic text segmentation. Text segmentation is important step in any NLP. In this paper, we discuss several methods dealing mainly with cases of ambiguity of Arabic text segmentation. Several conclusions have been made. These conclusions lead to make a proposal of text segmentation. A vis... View full abstract»

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  • A Named Entities Recognition System for Modern Standard Arabic using Rule-Based Approach

    Publication Year: 2015, Page(s):51 - 54
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (172 KB) | HTML iconHTML

    Named Entity Recognition (NER) is a task in Information Extraction (IE). The Named Entity Recognition has become very important for Natural Language Processing (NLP). In this paper, we designed a system which enhanced the named entities recognition for Arabic language where the system was developed for Arabic nouns and entities extractions. The nouns extraction system is based on Arabic morphologi... View full abstract»

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  • Combined Classification for Extracting Named Entities from Arabic Texts

    Publication Year: 2015, Page(s):55 - 60
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (262 KB) | HTML iconHTML

    In this paper, we describe an approach for extracting named entities from Arabic texts. Arabic language is hard to process since its characteristics that influence, even, the NE extraction. For our case, we consider that the named entities extraction can be assimilated to a typical classification problem. Indeed, this extraction consists of searching for text portions that can be classified in a N... View full abstract»

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  • Transducers Cascades for an Automatic Recognition of Arabic Named Entities in Order to Establish Links to Free Resources

    Publication Year: 2015, Page(s):61 - 67
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (206 KB) | HTML iconHTML

    Arabic named entities (ANE) are often sources of information. That is why they are used by several applications of natural language processing (NLP) mainly in information retrieval. In order to improve the relevance of the information obtained, links to free resources can be established. Indeed, the recognition of these entities requires the use of adequate formalisms. In this paper, we propose an... View full abstract»

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  • A System for Extracting Sentiment from Large-Scale Arabic Social Data

    Publication Year: 2015, Page(s):71 - 77
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (749 KB) | HTML iconHTML

    Social media data in Arabic language is becoming more and more abundant. It is a consensus that valuable information lies in social media data. Mining this data and making the process easier are gaining momentum in the industries. This paper describes an enterprise system we developed for extracting sentiment from large volumes of social data in Arabic dialects. First, we give an overview of the B... View full abstract»

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  • A Hybrid Approach for Sentiment Classification of Egyptian Dialect Tweets

    Publication Year: 2015, Page(s):78 - 85
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (239 KB) | HTML iconHTML

    Sentiment analysis has recently become one of the growing areas of research related to text mining and natural language processing. The main task of sentiment classification is to classify a sentence (i.e. tweet, review, blog, comment, news, etc.) as holding an overall positive, negative or neutral sentiment. Most of the current studies related to this topic focus mainly on English texts with very... View full abstract»

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  • Which Configuration Works Best? An Experimental Study on Supervised Arabic Twitter Sentiment Analysis

    Publication Year: 2015, Page(s):86 - 93
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (209 KB) | HTML iconHTML

    Arabic Twitter Sentiment Analysis has been gaining a lot of attention lately with supervised approaches being exploited widely. However, to date, there has not been an experimental study that examines how different configurations of the Bag of Words model, text representation scheme, can affect various supervised machine learning methods. The goal of the presented work is to do exactly that. Speci... View full abstract»

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  • Automatic Expandable Large-Scale Sentiment Lexicon of Modern Standard Arabic and Colloquial

    Publication Year: 2015, Page(s):94 - 99
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (154 KB) | HTML iconHTML

    In subjectivity and sentiment analysis (SSA), there are two main requirements are necessary to improve sentiment analysis effectively in any language and genres, first, high coverage sentiment lexicon - where entries are tagged with semantic orientation (positive, negative and neutral) - second, tagged corpora to train the sentiment classifier. Much of research has been conducted in this area duri... View full abstract»

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  • Lexicon Based and Multi-Criteria Decision Making (MCDM) Approach for Detecting Emotions from Arabic Microblog Text

    Publication Year: 2015, Page(s):100 - 105
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (240 KB) | HTML iconHTML

    Emotions serve as a communicative function both within the brain and within the social group. Most of previous opinion mining studies applied on Arabic microblog text to identify positive, negative or neutral polarity. This paper studies the problem of detecting multiple emotion classes in Arabic microblog text (e.g. Twitter). Incoming Arabic microblog text is classified into one of fine grained e... View full abstract»

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  • Increasing the Accuracy of Opinion Mining in Arabic

    Publication Year: 2015, Page(s):106 - 113
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1264 KB) | HTML iconHTML

    Opinion Mining is a raising research field of interest, with its different applications derived by market needs to analyze product reviews or to assess the public opinion, for political reasons, during presidential campaigns. In this paper, we address an approach for improving accuracy of Opinion Mining in Arabic. In order to conduct our study we need Arabic linguistic resources for opinion mining... View full abstract»

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  • Towards Analyzing Saudi Tweets

    Publication Year: 2015, Page(s):114 - 117
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (146 KB) | HTML iconHTML

    Recently Arabic dialects are receiving attention from the NLP research community due to their high usage in social media. One of the challenges of sentiment analysis of social media is the use of dialects. Since our ongoing research is on sentiment analysis of Saudi tweets, we conduct a pilot study to discover the percentage of Modern Standard Arabic (MSA) use by Saudi tweeters. The preliminary re... View full abstract»

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  • Identifying the Topic-Specific Influential Users Using SLM

    Publication Year: 2015, Page(s):118 - 123
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (194 KB) | HTML iconHTML

    Social Influence can be described as the ability to have an effect on the thoughts or actions of others. The objective of this research is to investigate the use of language in detecting the influential users in a specific topic on Twitter. From a collection of tweets matching a specified query, we want to detect the influential users from the tweets' text. The study investigates the Arabic Egypti... View full abstract»

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