Mervat Gheith

SENTIMENT ANALYSIS FOR MODERN STANDARD ARABIC AND COLLOQUIAL

The rise of social media such as blogs and social networks has fueled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations, therefore many are now looking to the field of sentiment analysis. In this paper, we present a feature-based sentence level approach for Arabic sentiment analysis. Our approach is using Arabic idioms/saying phrases lexicon as a key importance for improving the detection of the sentiment polarity in Arabic sentences as well as a number of novels and rich set of linguistically motivated features (contextual Intensifiers, contextual Shifter and negation handling), syntactic features for conflicting phrases which enhance the sentiment classification accuracy. Furthermore, we introduce an automatic expandable wide coverage polarity lexicon of Arabic sentiment words. The lexicon is built with gold-standard sentiment words as a seed which is manually collected and annotated and it expands and detects the sentiment orientation automatically of new sentiment words using synset aggregation technique and free online Arabic lexicons and thesauruses. Our data focus on modern standard Arabic (MSA) and Egyptian dialectal Arabic tweets and microblogs (hotel reservation, product reviews, etc.). The experimental results using our resources and techniques with SVM classifier indicate high performance levels, with accuracies of over 95%.

MIKA: A tagged corpus for modern standard Arabic and colloquial sentiment analysis

Sentiment analysis (SA) and opinion mining (OM) becomes a field of interest that fueled the attention of research during the last decade, due to the rise of the amount of internet documents (especially online reviews and comments) on the social media such as blogs and social networks. Many attempts have been conducted to build a corpus for SA, due to the consideration of importance of building such resource as a key factor in SA and OM systems. But the need of building these resources is still ongoing, especially for morphologically-Rich language (MRL) such as Arabic. In this paper, we present MIKA a multi-genre tagged corpus of modern standard Arabic (MSA) and colloquial. MIKA is manually collected and annotated at sentence level with semantic orientation (positive or negative or neutral). A number of rich set of linguistically motivated features (contextual Intensifiers, contextual Shifter and negation handling), syntactic features for conflicting phrases and others are used for the annotation process. Our data focus on MSA and Egyptian dialectal Arabic. We report the efforts of manually building and annotating our sentiment corpus using different types of data, such as tweets and Arabic microblogs (hotel reservation, product reviews, and TV program comments).

Idioms-Proverbs Lexicon for Modern Standard Arabic and Colloquial Sentiment Analysis

the fair amount of works in sentiment analysis (SA) and opinion mining (OM) systems in the last decade and with respect to the performance of these systems, but it still not desired performance, especially for morphologically-Rich Language (MRL) such as Arabic, due to the complexities and challenges exist in the nature of the languages itself. One of these challenges is the detection of idioms or proverbs phrases within the writer text or comment. An idiom or proverb is a form of speech or an expression that is peculiar to itself. Grammatically, it cannot be understood from the individual meanings of its elements and can yield different sentiment when treats as separate words. Consequently, In order to facilitate the task of detection and classification of lexical phrases for automated SA systems, this paper presents AIPSeLEX a novel idioms/ proverbs sentiment lexicon for modern standard Arabic (MSA) and colloquial. AIPSeLEX is manually collected and annotated at sentence level with semantic orientation (positive or negative). The efforts of manually building and annotating the lexicon are reported. Moreover, we build a classifier that extracts idioms and proverbs, phrases from text using n-gram and similarity measure methods. Finally, several experiments were carried out on various data, including Arabic tweets and Arabic microblogs (hotel reservation, product reviews, and TV program comments) from publicly available Arabic online reviews websites (social media, blogs, forums, e-commerce web sites) to evaluate the coverage and accuracy of AIPSeLEX.

A Requirements Elicitation Approach for Cloud Based Software Product Line ERPs

Implementing Enterprise Resource Planning (ERP) systems in business organizations aims to integrate all business units of an organization. Configuring and customizing ERP systems are the main challenges that face the implementation process. ERP systems contain many similar modules and units which can be implemented for most of the ERP systems. Software Product Lines (SPLs) as a trend in software engineering is very promising, as it can offer a lot of facilities and benefits for all types of stakeholders. Building SPLs for ERP systems will affect the implementation process of ERP systems and will increase the flexibility of configuration and customization. Moreover, moving ERPs to the cloud will facilitate the implementation process and will affect the Return On Investment (ROI) due to scalability plans in cloud services. This research introduces an SPLs requirements elicitation approach for cloud ERP systems. This approach combines the principles of SPLs with ERP systems in the cloud environment.

A SURVEY OF ARABIC DIALOGUES UNDERSTANDING FOR SPONTANEOUS DIALOGUES AND INSTANT MESSAGE

Building dialogues systems interaction has recently gained considerable attention, but most of the resources and systems built so far are tailored to English and other Indo-European languages. The need for designing systems for other languages is increasing such as Arabic language. For this reasons, there are more interest for Arabic dialogue acts classification task because it a key player in Arabic language understanding to building this systems. This paper surveys different techniques for dialogue acts classification for Arabic. We describe the main existing techniques for utterances segmentations and classification, annotation schemas, and test corpora for Arabic dialogues understanding that have introduced in the literature

Towards Understanding Egyptian Arabic Dialogues

Labelling of users utterances to understanding his attends which called Dialogue Act (DA) classification, it is considered the key player for dialogue language understanding layer in automatic dialogue systems. In this paper, we proposed a novel approach to users utterances labeling for Egyptian spontaneous dialogues and Instant Messages using Machine Learning (ML) approach without relying on any special lexicons, cues, or rules. Due to the lack of Egyptian dialect dialogue corpus, the system evaluated by multi-genre corpus includes 4725 utterances for three domains, which are collected and annotated manually from Egyptian call-centers. The system achieves F1 scores of 70. 36% overall domains.

An Enhanced Arabic OCR Degraded Text Retrieval Model

This paper provides a new model enhancing the Arabic OCR degraded text retrieval effectiveness. The proposed model based on simulating the Arabic OCR recognition mistakes on a word based approach. Then the model expands the user search query using the expected OCR errors. The resulting expanded search query gives higher precision and recall in searching Arabic OCR-Degraded text rather than the original query. The proposed new model showed a significant increase in the degraded text retrieval effectiveness over the previous models. The retrieval effectiveness of the new model is %97, while the best effectiveness published for word based approach was %84 and the best effectiveness for character based approach was %56. In addition, the new model overcomes several limitations of the current two existing models.

Appraisal and Analysis of Various Self-Adaptive Web Service Composition Approaches

Service-Oriented Requirements Engineering (SORE ) plays a significant role in eliciting, specifying, and validating service requirements that will be developed by Web service technology . With the increasing complexity of users’ requirements, Web services need to be combined together to fulfill them. The process of building new value-added services by integrating sets of existing Web services to satisfy users’ requirements is called Web Service Composition (WSC). The main objective of WSC is to develop composite services to satisfy users’ requirements, which does not only include Functional Requirements (FR), but also Non-Functional Requirements (NFR). One of the main challenges of WSC is how it deals with dynamic environments. Since the Web service properties and composition requirements are frequently changeable, this demands that SORE activities must be equipped with a self-adaptation mechanism to provide the most appropriate composite services and satisfy users’ requirements emerged. Self-adaptation occurs in either a proactive or reactive manner. In this chapter, we appraise and analyze existing reactive adaptation research that deals with the problem of WSC in a dynamic environment in order to identify the research gaps in this field. These approaches are classified into three categories: used of variability models, context-awareness, and multi-agent approaches. Most of these approaches are not able to deal with continuous and unanticipated changes in complex uncertain contexts because they need to define the contexts in design time. It is usually difficult to predict all of the possible situations that might arise in an uncertain environment.

Automating Requirements Elicitation of Cloud-Based ERPs

Cloud computing (CC) imposed its presence in various domains as a computing model based on what it offers for enterprises. ERP systems as a domain is one of the beneficiary domains of SaaS applications. Eliciting requirements for cloud ERP systems is a challenging process due to the complex nature of ERP systems in addition to the distributed nature of CC. Most of the current techniques for eliciting ERP requirements do not take into consideration working in cloud environments. This paper is concerned with automating the requirements elicitation process for cloud-based ERPs. It also presents an interactive prototype to be used in a distributed environment, which uses the principals of the Form-Based Model (FBM). We use a real-life case study to demonstrate the automation process.

Serious Educational Games’ Ontologies: A Survey and Comparison

Serious Educational Games (SEGs) are games not having a mere purpose of entertainment. They benefit from the main characteristics of games, such as engagement and immersiveness to achieve pedagogic objectives. In spite of the promising results of SEGs reported in the literature, their analysis and design still require complex tasks that incorporate game design activities within an educational context. Ontologies that include concepts, relations, and governing rules for both games and education domains could offer an approach to solve such problem. An ontology, as a domain modeling tool, could be used as a meta-model to guide a SEG designer, in addition to bridging the communication gap between the game design and pedagogic domains. This paper presents a survey of available ontologies for SEGs in the literature, in addition to comparing them. We managed to find only two SEGs’ ontologies and a meta-model in the literature, and hence presented and compared them. After presenting the survey, and result analysis and general comparison, we followed an ontologies’ comparison method called OntoMetric for further evaluation of the current SEGs’ ontologies. Our research results revealed that SEGs’ ontologies in the literature have two main diverse perspectives. One perspective intensively focuses on the game domain concepts, and the other perspective focuses on the pedagogic domain concepts. In addition, there is little proof that a comprehensive web-based SEGs ontology, which is characterized by completion, consistency, and reusability exists.