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... more
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 the response. This paper is dedicated to discuss the system architecture for the conversational agent and explain each component in details.
Natural language processing (NLP) has many applications such as database user interfaces, machine translation, knowledge acquisition and report abstraction. Several approaches have been used in dealing with NLP. We describe an ongoing... more
Natural language processing (NLP) has many applications such as database user interfaces, machine translation, knowledge acquisition and report abstraction. Several approaches have been used in dealing with NLP. We describe an ongoing research project about understanding natural language input using multiagent system techniques. The system combines between a lexical structural approach and a cognitive structural approach. The lexical structural contains
Research Interests: Natural Language Processing, Machine Translation, User Interface, Multi Agent System, Multi Agent Systems, and 10 moreUser interfaces, Natural language, Knowledge Acquisition, Text to Speech, Language Translation, Natural Language Understanding, Speech to Text, Cognitive Structure, Multiagent System, and Natural Languages
Natural Language Processing (NLP) has many applications such as Database user interfaces, Machine Translation, Knowledge Acquisition and Report Abstraction. Several approaches have been used in dealing with NLP. This paper describes an... more
Natural Language Processing (NLP) has many applications such as Database user interfaces, Machine Translation, Knowledge Acquisition and Report Abstraction. Several approaches have been used in dealing with NLP. This paper describes an ongoing research project about understanding natural language text using object-oriented techniques. It starts with a brief introduction to the object-oriented paradigm and natural language processing. A description of the project, its different modules, and an example of text understanding are presented. The uses of object-oriented techniques in knowledge representation and morphological analysis are described.
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Internet of Things (IoT) networks have developed tremendously over the past years. The main concept behind this technology is to facilitate information exchange between devices without human intervention. However, the eccentric and... more
Internet of Things (IoT) networks have developed tremendously over the past years. The main concept behind this technology is to facilitate information exchange between devices without human intervention. However, the eccentric and heterogeneous nature of this type of network demands certain security requirements and algorithms that differ from those implemented in traditional networks. Recently, several studies have explored the use of Machine Learning and Deep Learning methodologies to overcome the security problems in IoT networks and preserve data privacy. This paper explores the diverse security threats and challenges existing in IoT networks. It reviews some learning-based Intrusion Detection Systems that are proposed as countermeasures to many consequent security breaches in IoT environments such as Denial of Service, spoofing, or eavesdropping attacks.
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... more
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 the computer player through exchanging new cases among engines case-based reasoning systems. We believe this will reveal game players from downloading a new engine of the game and loosing their saved episodes.
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The field of research in ontology engineering appears to be mature, considering the vast number of contemporary methods and instruments for the formalization and application of knowledge representation models. However, the evolutionary... more
The field of research in ontology engineering appears to be mature, considering the vast number of contemporary methods and instruments for the formalization and application of knowledge representation models. However, the evolutionary aspects of ontologies are still little understood and supported. This is especially important in distributed and collaborative settings like the Semantic web, where ontologies naturally co-operate with their user communities. Various organizations and teams are building common ground in this context. Ontology is instrumental in this process through the formal description of shared knowledge. Such semanticity constitutes a sound basis for defining, sharing (business) objectives and interests and eventually developing useful collaborative services and systems. In this "complex" and dynamic environment, a collaborative model for process change requires more powerful methodologies for engineering, argumentation and negotiation. Software Engineering provides teamwork, team management, feedback management, versioning, merging, and evolving software artifacts with a wealth of techniques and tools. Many of these techniques can be used again in an ontology engineering environment. This paper examines how this problem can be resolved using Scrum and Nexus frameworks, which are among the most robust models for software development.
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The Semantic Web is an incomplete dream so far, but a revolutionary platform as Blockchain could be the solution to this, not optimal reality. There is still little understanding of, and support for, the evolutionary aspects of... more
The Semantic Web is an incomplete dream so far, but a revolutionary platform as Blockchain could be the solution to this, not optimal reality. There is still little understanding of, and support for, the evolutionary aspects of ontologies. This is particularly crucial in distributed and collaborative settings such as the Semantic Web, where ontologies naturally co-evolve with their communities of use. In this setting, different organizations and teams collaboratively build a common ground of the domain. In this "complex" and dynamic setting, a collaborative change process model requires more powerful engineering, argumentation and negotiation methodologies. Blockchain offers a robust framework for teams' collaboration and ontology versioning globally between an infinite number of teams. Blockchain is an example of a distributed computing system with high Byzantine fault tolerance. This makes blockchains potentially suitable for the recording of evolution events, ontolo...
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Intelligent techniques have been used in the marketing and sales sectors of business toimprove analysis, increase revenues and save time. In customer-centric institutions, one of the areas inwhich intelligent techniques and data mining... more
Intelligent techniques have been used in the marketing and sales sectors of business toimprove analysis, increase revenues and save time. In customer-centric institutions, one of the areas inwhich intelligent techniques and data mining algorithms have been used is the personalization forenhanced CRM (customer relationship management) performance. However, with a growing number ofcustomers, the diversity of products on offer, the complex behavior of customer groups and thecontinuous change of personalization parameters, the production of a tailored personalizedrecommendation and the prediction of future needs are a challenging task. Within these institutions,personalization that is more true to the customer needs leads to better targeted marketing campaignsand enhances customer satisfaction with the ultimate aim of increasing the rates of customer retention,and improving competitive advantage. Intelligent techniques and data mining algorithms have beenused to produce a more accuratel...
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The semantic representation of different medical information enables the medical information system to understand the meaning of medical terms. Ontology is used as a semantic representation technique that organizes and represents the... more
The semantic representation of different medical information enables the medical information system to understand the meaning of medical terms. Ontology is used as a semantic representation technique that organizes and represents the semantic relations between the medical terms. Rheumatoid disease is one of the common autoimmune diseases; it has several clinical findings and several treatments to control its activity. This paper presents a new ontology building methodology that enables the ontology engineer to represent all types of knowledge and the intervention of experts from earlier stages. In addition, the paper presents the development of rheumatoid ontology that covers the major clinical aspects of the disease.
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Ontology evolution is defined as the process of updating the ontology according to the changes in the domain. Current ontology evolution techniques in the medical domain focus on the consistency after the ontology evolution and ignore it... more
Ontology evolution is defined as the process of updating the ontology according to the changes in the domain. Current ontology evolution techniques in the medical domain focus on the consistency after the ontology evolution and ignore it during the evolution process. This paper presents a novel evolution system that takes into account the ontology consistency. It relies on the use of standard medical resources that reflect the changes that are occurred in the medical domain. Moreover, the system makes use of a database that contains the scientific and Egyptian commercial names of medicine used in autoimmune diseases.
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... more
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 from the text automatically. This Process would save effort and time. Text mining considered as a subset of data mining where data mining is more generic. This paper proposes a methodology of mining a text for a case study related to publication papers. Some of text mining approaches will be introduced for mining the publication papers using machine learning (ML) and natural language processing (NLP) techniques. Describing each phase as following: First phase is keywords extraction using natural language processing techniques, second phase named entity recognition and last phase is document classification. The last two phases are using th...
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The growth of medical applications that work with ontologies in health enterprises creates the need to ensure the integration and semantic homogeneity between them. In order to provide the reliable knowledge (in terms of new treatments,... more
The growth of medical applications that work with ontologies in health enterprises creates the need to ensure the integration and semantic homogeneity between them. In order to provide the reliable knowledge (in terms of new treatments, new clinical findings, new exercises), medical ontologies should be evolved. The adaptation of ontology according to the changes in domain of interest is called ontology evolution. This paper investigates ontology evolution approaches applied in medical domain. It also presents a framework proposal for comparative study that demonstrates the difference between the approaches. Keywords— Ontology engineering, Ontology evolution, Ontology enrichment, Ontology population.
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Page 1. APPL A COMPARISON OF COMPILED REASONING SYSTEMS AND MODEL-BASED REASONING SYSTEMS AND THEIR .ICABILITY TO THE DIAGNOSIS OF AVIONICS SYSTEMS James K. McDowell and James F. Davis of The Ohio State University Columbus, OH ...
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Intelligent techniques have been used in the marketing and sales sectors of business to improve analysis, increase revenues and save time. In customer-centric institutions, one of the areas in which intelligent techniques and data mining... more
Intelligent techniques have been used in the marketing and sales sectors of business to improve analysis, increase revenues and save time. In customer-centric institutions, one of the areas in which intelligent techniques and data mining algorithms have been used is the personalization for enhanced CRM (Customer Relationship Management) performance. However, with a growing number of customers, the diversity of products on offer, the complex behavior of customer groups and the continuous change of personalization parameters, producing a tailored personalized recommendation that predicts their future needs is a challenging task. In this paper, we propose multi dimension personalization framework architecture to improve personalized targeting. The framework presented improves on the automation of existing systems by using multiple supervised and unsupervised data mining techniques, and enhances the level of targeting by considering more effective dimensions in multiple stages of the framework. A theoretical case study explaining the practical working and perceived advantages of the new framework is presented.
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Real-time strategy games are strategic war games where two or more players operate on a virtual battlefield, controlling resources, buildings, units and technologies to achieve victory by destroying others. Achieving victory depends on... more
Real-time strategy games are strategic war games where two or more players operate on a virtual battlefield, controlling resources, buildings, units and technologies to achieve victory by destroying others. Achieving victory depends on selecting a suitable plan (set of actions), selecting a suitable plan depends on building an imagination (building a model) of the opponent to know how to deal with. This imagination is the opponent model, the stronger the opponent modelling process is, the more accurate the selected suitable plan is and consequently the higher probability achieving the victory is. One of the environment's challenges in real-time strategy games is that classifying the opponent model is game specific. This paper introduces a new methodology through which we can classify the observed opponent model in a way that is not game specific. Our methodology includes two paths, only one of them is executed per real-time strategy game type (per opponent models trained), which means that different type of real-time strategy games will execute different paths of the two paths of our methodology.
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eXtensible Markup Language (XML) is one of the standard data representation nowadays. It can be used in various applications as its flexibility and easy to use so the need to summarize XML document become increasingly an important topic... more
eXtensible Markup Language (XML) is one of the standard data representation nowadays. It can be used in various applications as its flexibility and easy to use so the need to summarize XML document become increasingly an important topic to save time and cost. For these reasons, there are more interest for developing tools for summarizing XML Documents. This paper surveys different approaches for summarizing XML documents regarding to both its structure and content.
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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... more
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 important parts in both Information Retrieval (IR) like search engines and Question Answering (QA). Also, these semantic resources should be available, readable and understandable. Through the semantic web, ontologies play a central role to support the search engine process. In recent years, a lot of researchers are concerned in building Arabic ontologies, which can be exploited by others. This paper investigates the current studies on the ontological engineering approach and ontology techniques for the Holy Quran by comparing the general criteria such as ontology construction, the domain name in the Quran, and the availability in search index. Finally, this paper concludes that there are a lot of researchers presents the ontology in specific domain in the Quran and tried to develop an upper ontology, but it is not complete and did not use semantic technology.
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Ontology has been increasingly recognised as an instrumental artifact to help make sense of large amounts of data. However, the challenges of Big Data significantly overburden the process of ontology storage and query particularly. In... more
Ontology has been increasingly recognised as an instrumental artifact to help make sense of large amounts of data. However, the challenges of Big Data significantly overburden the process of ontology storage and query particularly. In this respect, the paper aims to convey considerations in relation to improving the practice of storing or querying large-scale ontologies. Initially, a systematic literature review is conducted with the aim of thoroughly inspecting the state-of-the-art in literature. Subsequently, a graph database-oriented approach is proposed, considering ontology as a large graph. The approach endeavours to address the limitations encountered within traditional relational models. Furthermore, scalability and query efficiency of the approach are verified based on empirical experiments using a subset of Freebase data. The Freebase subset is utilised to build a large-scale ontology graph composed of more than 500K nodes, and 2M edges.
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Information are provided in heterogeneous terms in several forms (document, database and ontology), it is necessary to integrate them to facilitate the information retrieval and knowledge discovery. Moreover, the semantic representation... more
Information are provided in heterogeneous terms in several forms (document, database and ontology), it is necessary to integrate them to facilitate the information retrieval and knowledge discovery. Moreover, the semantic representation of term helps the computer to understand the meaning of information. Information of a specific domain can be presented in different terms, the matching between terms achieves the goal to represent an integrate information. One of the domains which need the integration between its terms is the medical domain. This paper presents a survey on the major term matching techniques in the medical domain.
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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... more
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 structure and writing styles. Our work is a part of an ongoing research to create an abstractive summary for a single input document in the Arabic Language. The abstractive summary is generated through three modules; converting the input Arabic text into an RSG, then performing Graph Reduction, and finally generating the summarized text from the reduced graph. This is achieved with the aid of a domain Ontology. In this paper, we are illustrating the architecture of the third module, which works on generating Arabic text from RSG using Ontology.
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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... more
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 Retrieval and Natural Language Processing applications like search engines, question answering, machine translation, etc. In recent years, many researchers are interested in building Arabic sematic resources, which are then can be exploited by others to build Arabic sematic applications. Recently, a proposed ontological model for “Time Nouns” vocabulary in the Holy Quran was introduced. To share towards building an integrated and unified ontology for Arabic language, in this paper, we are proposing an ontology-based model for Arabic language vocabulary associated with “Place Nouns” in the Holy Quran. This ontology is represented by the Web Ontology Language (OWL), which is the standard language for the semantic web. The ontology will be useful in the knowledge of the Islamic learning, linguistics researches, and Semantic Web applications.
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The abstract should contain the objectives of the research, its main findings and principle conclusions. Maximum length should not exceed 200 words., The abstract should be typed single-spaced and both-sides justified within a centered... more
The abstract should contain the objectives of the research, its main findings and principle conclusions. Maximum length should not exceed 200 words., The abstract should be typed single-spaced and both-sides justified within a centered width of 14 cm. A "Times Roman" font type or similar is expected to be used with 14 point bold for the title, 12 point bold for headings and authors names, 10 points normal for the abstract, affiliations, and reference list and 12 points normal for the text and rest items.
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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... more
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 human life, the environment, and properties, there is no generic methodology for developing such systems based on standards and guidelines. Safety analysis for SCSSs is the second phase in our methodology. This methodology sets an integrated model that concerned about the safety of critical software systems as a component of the critical systems. It consists of the needed processes required for developing SCSSs free of faults. This methodology ensures that SCSSs are developed using processes based on appropriate standards and guidelines and can be accordingly certified. The objective of this methodology is to produce certified critical so...