Mostafa Aref

• Ain Shams University

One of the fundamental and challengeable research areas in Real Time Strategy (RTS) games is opponent modelling. Most current approaches to opponent modelling pretended inefficiency. They are either computationally expensive or required a numerous amount of online gameplays to start learn successful models. Unfortunately, most successful approaches...

Representing Arabic Text semantically using Rich Semantic Graph (RSG) is one of the recent techniques that facilitate the process of manipulating the Arabic Language in Natural Language Processing (NLP) field. The work presented in this paper is a part of an ongoing research to create an abstractive summary for a single input document in Arabic Lan...

Arabic Text Summarization is one of the challenging open areas for research in Natural Language Processing (NLP) field. Representing Arabic text semantically can facilitate this process by helping in understanding the highly complicated semantic structure of the Arabic language. The work presented in this paper is a part of an ongoing research to c...

Recently Safety Critical Software Systems (SCSSs) become essential part of many critical systems such as Nuclear Power Plants (NPPs), radiation therapy, aircrafts, and many medical devices. Although of the vital role of SCSSs in saving human life, environment, and properties, there is no generic methodology for developing such systems based on stan...

One of the important Natural Language Processing applications is Text Summarization, which helps users to manage the vast amount of information available, by condensing documents’ content and extracting the most relevant facts or topics included. Text Summarization can be classified according to the type of summary: extractive, and abstractive. Ext...

This research examines how various imputation methods and deep learning models influence water quality forecasting by utilizing time-series sensor data from Galicia, Spain. We evaluated the advanced SAITS imputation model against traditional Median and KNN techniques across various targets-pH, Dissolved Oxygen (DO), Total Ammonium (NH₄⁺), and Bioch...

Water quality plays a pivotal role in ensuring the safety and sustainability of water resources, with significant implications for environmental protection, public health, and various industrial applications. This paper presents both a review of related state-of-the-art works and an implementation and application of adapted versions of these relate...

Voice Conversion (VC) is the task of changing the speaker characteristics in a source speech signal to be like the one in a target speech while keeping the linguistic content of the source. VC is widely used in many applications such as speaking assistance systems for people with vocal disorders. Non-parallel many-to-many and non-parallel zero-shot...

Recent advancements in generative artificial intelligence have boosted significant interest in conversational agents. The visual dialog task, a synthesis of visual question-answering and dialog systems, requires agents capable of both seeing and chatting in natural language interactions. These agents must effectively understand cross-modal contextu...

In recent years, interest in vision-language tasks has grown, especially those involving chart interactions. These tasks are inherently multimodal, requiring models to process chart images, accompanying text, underlying data tables, and often user queries. Traditionally, Chart Understanding (CU) relied on heuristics and rule-based systems. However,...

The proliferation of Internet of Things (IoT) devices has become inevitable in contemporary life, significantly affecting myriad applications. Nevertheless, the pervasive use of heterogeneous IoT gadgets introduces vulnerabilities to malicious cyber-attacks, resulting in data breaches that jeopardize the network’s integrity and resilience. This stu...

With the exponential rise of Internet of Things (IoT) devices in our modern-day lifestyle, the potential danger of botnet intrusions has become inevitable. These botnet attacks cause extensive damage to both individual users and large organizations. In the realm of IoT botnet intrusion detection, learning-based Intrusion Detection Systems (IDS) wer...

Arabic is a language with rich morphology and few resources. Arabic is therefore recognized as one of the most challenging languages for machine translation. The study of translation into Arabic has received significantly less attention than that of European languages. Consequently, further research into Arabic machine translation quality needs mor...

Sentiment Analysis, also known as opinion mining, is the area of Natural Language Processing that aims to extract human perceptions, thoughts, and beliefs from unstructured textual content. It has become a useful, attractive, and challenging research area concerning the emergence and rise of social media and the mass volume of individuals’ reviews,...

Sentiment analysis is one of the biggest challenges for mining textual online content generated by users. This paper concentrates on reviews and feedback from customers, which are relevant content types representing opinions. The aim of this work is to identify the semantic orientation of each sentence (e.g. positive or negative). Traditional metho...

In the software development process, more than one developer may work on developing the same program and bugs in the program may be fixed by a different developer; therefore, understanding the source code is an important issue. Pseudocode plays an important role in solving this problem, as it helps the developer to understand the source code. Recen...

Generating source code is necessary especially as software evolves in complexity and demand. Finding a mechanism to generate the source code according to the requirements will save time for developers at the stage of development of the software. In this paper, a mechanism is proposed to generate the source code based on the database schema and user...

Forecasting is one of the useful applications of machine learning in Enterprise Resource Planning (ERP). This is a vital component of a business's financial planning, which projects into the future using data from the past. This study offers a novel method for anticipating purchases using time series data. Based on prior order requests, the suggest...

Biological taxonomic classification is an important task needed for the identification and discovery of organisms, as well as the inference of their evolutionary relationships. The order and structure of biological sequence components has an essential and primary role in what the sequence’s identity and function is. In order to be able to efficient...

Machine learning in an Enterprise Resource and Planning (ERP) system allows a business to save, organize, and analyze data to make better decisions and obtain valuable views that were previously inconceivable. Forecasting is one of the most common applications of machine learning in ERP. This is a crucial part of a company’s financial planning, whi...

The comprehension of source code is very difficult, especially if the programmer is not familiar with the programming language. Pseudocode explains and describes code contents that are based on the semantic analysis and understanding of the source code. In this paper, a novel retrieval-based transformer pseudocode generation model is proposed. The...

The conversational agents is one of the most interested topics in computer science field in the recent decade. Which can be composite from more than one subject in this field, which you need to apply Natural Language Processing Concepts and some Artificial Intelligence Techniques such as Deep Learning methods to make decision about how should be th...

Automated personality detection attracts researchers nowadays. Realizing personality aid in many domains like social media to attract users. Models that are used in personality detection, lack understanding of personality deeply. Enneagram is a personality model to know motivations, desires, and fears. Psychiatrists uses Enneagram. Enneagram gives...

Understanding the content of the source code and its regular expression is very difficult when they are written in an unfamiliar language. Pseudo-code explains and describes the content of the code without using syntax or programming language technologies. However, writing Pseudo-code to each code instruction is laborious. Recently, neural machine...

Efficient real-time clustering is a relevant topic in big data streams. Data stream clustering needs necessarily a short time execution frame with bounded memory utilizing a one-scan process. Because of the massive volumes and dynamics of data streams, parallel clustering solutions are urgent. This paper presents a new approach for this trend, with...

Biological sequence classification is a key task in Bioinformatics. For research labs today, the classification of unknown biological sequences is essential for facilitating the identification, grouping and study of organisms and their evolution. This work focuses on the task of taxonomic classification of bacterial species into their hierarchical...

Video captioning is a recent emerging task that describes a video through generating a natural language sentence. Practically videos are untrimmed where both localizing and describing the event of interest is crucial for many vision based- real life applications. This paper proposes a deep neural network framework for effective video event localiza...

Social Media Networks are one of the main platforms to express our feelings. The emotions we put in text tell a lot about our behavior towards any topic. Therefore, the analysis of text is a need for detecting one’s emotions in many fields. This paper introduces a deep learning model that classify sentiments from tweets using different types of wor...

Sentiment analysis is the task of identifying opinions expressed in any form of text. With the widespread usage of social media in our daily lives, social media websites became a vital and major source of data about user reviews in various fields. The domain of tourism extended activity online in the most recent decade. In this paper, an approach i...

Mining in data streams has been a hot research topic in the recent time. A main challenge in data stream mining lies in extracting knowledge in real time from a massive, dynamic data stream in only a single scan. Data stream clustering presents an important role in data stream processing. This paper proposes SCluStream an algorithm for tracking clu...

The amount of data that produced is increased day after day especially data as a text, so with this massive production it would be difficult to analyze or extract information to discover the patterns from the unstructured text. Text mining is used for availing the massive amount of knowledge that is in the text and deriving high quality information...

Biological sequence classification is a key task in Bioinformatics. For research labs today, the classification of unknown biological sequences is essential for facilitating the identification, grouping and study of organisms and their evolution. This paper compares three of the most recent deep learning works on the 16S rRNA barcode dataset for ta...

Most of query translation disambiguation approaches rely on a parallel corpus to resolve the translation ambiguity. This is because parallel corpus are good resources for resolving translation ambiguity. However, they have limitations in translating with a low convergence, specific domain, handling multi-word expressions, and non-availability in al...

Biological sequence classification is a key task in Bioinformatics. For research labs today, the classification of unknown biological sequences is essential for facilitating the identification, grouping and study of organisms and their evolution. This paper compares three of the most recent deep learning works on the 16S rRNA barcode dataset for ta...

Mining in data streams has been a hot research topic in the recent time. A main challenge in data stream mining lies in extracting knowledge in real time from a massive, dynamic data stream in only a single scan. Data stream clustering presents an important role in data stream processing. This paper proposes SCluStream an algorithm for tracking clu...

Psychologists are interested in predicting the personality traits of individuals, which costs them great effort. The researchers in the field of computer science have found in the social media platforms an easier way achieve these studies. As they are widespread and used by most individuals. Social media enables people to share most of their though...

The cartography of danger has recently expanded to turn several hotspots worldwide. This proves true when it comes to the Middle East where military interventions escalate and internal conflicts leverage. Implicating on the folkloric perception of the real geostrategic threats, this paper uses linguistic cues to explore the conceptualization of geo...

We introduce a method for measuring the quantity of online content of a set of languages at domain level. This measurement is used for building a Multi-Lingual Information Retrieval (MLIR) system that identifies which languages are strongly represented on the internet about a specific query topic. The system architecture includes two modules; the o...

Source Code Generation (SCG) is the sub-domain of the Automatic Programming (AP) that helps programmers to program using high-level abstraction. Recently, many researchers investigated many techniques to access SCG. The problem is to use the appropriate technique to generate the source code due to its purposes and the inputs. This paper introduces...

Sentiment analysis and emotion recognition are major indicators of society trends toward certain topics. Analyzing opinions and feelings helps improving the human-computer interaction in several fields ranging from opinion mining to psychological concerns. This paper proposes a deep learning model for emotion detection from short informal sentences...

The constructed medical ontologies need to be updated in order to reflect the changes occurred on the medicine such as the clinical findings, treatments and their side effects. Various researchers defined the ontology maintenance as the process of updating the ontology or the evolution of the ontology. Other researches consider the ontology mainten...

This paper proposes a description of the bilingual ontology (Arabic-English) by using a class of object oriented programming to define a concept of noun and verb. Describe the bilingual hierarchy of noun and verb concepts. We have designed a three algorithms of corpus based for bilingual ontology such as: preprocessing, (matching & alignment) and u...

Ontology is the gateway for the interaction between human and the machines because it facilitates the gaining of the information for the end users. The semantic web terms and vocabulary are considered as form of ontology. So the improvement of the ontology helps in the semantic web progration. Arabic ontology is a critical natural language processi...

The world of Big Data continues to expand, and forge the landscape of data analytics. Datasets are rapidly growing in size and complexity, and there is a pressing need to develop solutions that can harness this deluge of data to produce useful insights. Unsupervised techniques, such as clustering, present as appropriate methods for exploring and su...

Social media domain has its own terms, phrases, grammar, and emoticons. Text mining and analysis needs specific natural languages techniques as well as specific ontology that include slang terms and expressions. Moreover, the discovery of new information from the social media forums can be applied through the matching between slang terms, expressio...

The semantic resources are important parts in the Information Retrieval (IR) such as search engines, Question Answering (QA), etc., these resources should be available, readable and understandable. In semantic web, the ontology plays a central role for the information retrieval, which use to retrieves more relevant information from unstructured inf...

Visualisation is attaining a growing recognition as a pivotal part of the data analysis process. Visualisation-based solutions are increasingly used to adequately explore and communicate understanding of large-scale datasets. This paper presents a web-based visualisation tool, named FreebaseViz, for visually exploring the schema of Freebase. The vi...

Ontology is an explicit specification of conceptualization. It defines the terms with specified relationships between them and can be interpreted by both humans and computers. In general, there are scare semantic resources for Arabic language especially in Arabic ontologies. These semantic resources are very essential components in both Information...

The Arabic language is the spoken language in the Semitic languages groups, which is spoken by more than 422 million people. It is the language of the Islamic Holy Quran, so all the Muslims should learn it. In general, there is a shortage in semantic resources for the Arabic language especially in Arabic ontologies. These semantic resources are imp...

Text Generation is a challenging task in Natural Language Processing (NLP). Its purpose is to generate grammatically correct text from machine representation source such as a knowledge base. One of the most recent semantic representation is Rich Semantic Graph (RSG). It exploits not only the semantic representation techniques but also the Language...

Information Extraction (IE) is one of the most important Natural Language Processing (NLP) applications, which extracts information such as Named-Entities (NE) and collocation of terms from the corpus. Collocation is a sequence of terms that co-occur together in the corpus. In Arabic Information Extraction, there are many problems because of the co...

One of the important Natural Language Processing applications is Text Summarization, which helps users to manage the vast amount of information available, by condensing documents’ content and extracting the most relevant facts or topics included. Text Summarization can be classified according to the type of summary: extractive, and abstractive. Ext...

Information Extraction (IE) is one of the most important Natural Language Processing (NLP) applications, which extracts information such as Named-Entities (NE) and collocation of terms from the corpus. Collocation is a sequence of terms that co-occur together in the corpus. In Arabic Information Extraction, there are many problems because of the co...

In recent years the use of Safety Critical Software Systems (SCSSs) has been increased in many critical systems such as Nuclear Power Plants (NPPs), radiotherapy, aircrafts, and many medical devices. These systems rely on the use of safety critical software in controlling and monitoring critical devices. Despite of the vital role of SCSSs in saving...

Natural Language Generation (NLG) focuses on the generation of written texts in natural language from some underlying semantic representation of information. A new semantic representation called Rich Semantic Graph (RSG) has been proposed to be used as an intermediate representation during recent research for Natural Language processing application...

For many years, researchers tried and succeeded to develop agents that can adapt their behavior to face new opponent scenarios and beating them. So in this paper we introduce an experience exchanging model that allow a game engine to update all other engines with the game reaction against new surprising un-programmed opponent scenarios that face th...