Abstract Since its emergence in 1997, Extensible Markup Language (XML) has become a standard data format for data exchange among a variety of web applications. In this paper, we present a framework to effectively evaluate XML queries in a visual environment. We have developed a system termed VXPath, which is a visual XPath query evaluator that allows the user to evaluate various XPath queries by clicking the nodes... Since its emergence in 1997, Extensible Markup Language (XML) has become a standard data format for data exchange among a variety of web applications. In this paper, we present a framework to effectively evaluate XML queries in a visual environment. We have developed a system termed VXPath, which is a visual XPath query evaluator that allows the user to evaluate various XPath queries by clicking the nodes in an expanding tree instead of typing the whole XPath queries manually. Our system GUI is built on top of Microsoft .NET Windows Forms Applications. We have implemented most XPath axes in our system, including child, descendant, self, parent, ancestor, following-sibling, preceding- sibling, predicate and so on. In order to handle large size XML documents, instead of loading the whole XML document into memory, we developed an effective algorithm to extract a concise data synopsis called structural summary from the original XML document to avoid the loading overhead for large XML documents. We evaluated our system over the data from XMark and DBLP and our system can handle large XML documents up to gigabytes. Read More Read Less

Abstract Time series analysis is one of the major techniques in capturing trends and pattern of the occurrence for future forecasting. Existing but scarce works have developed temporal-based techniques which target to either predict movement (increase or decrease) or quantify the possibility of the predicted event to happen. Many of these techniques focus on the values of the time series attribute but there is no available work on... Time series analysis is one of the major techniques in capturing trends and pattern of the occurrence for future forecasting. Existing but scarce works have developed temporal-based techniques which target to either predict movement (increase or decrease) or quantify the possibility of the predicted event to happen. Many of these techniques focus on the values of the time series attribute but there is no available work on dengue or intrusion logs that focus on temporal trend analysis-based on temporal relations mining. In this work the proposed technique utilize the temporal trends analysis of the observational attributes towards the pattern of the target's attribute values. In this work, we propose a new temporal trends analysis approach that uses temporal relation mining in forecasting dengue outbreak and cyber intrusion. We leverage the temporal abstractions and temporal logic to define patterns with the goal to optimize prediction accuracy. From the experiment conducted, the results showed that the proposed approach has better prediction as compared to the baseline. Read More Read Less

Abstract Today the security aspect is a backbone of every computer system, particularly when this system contains sensitive information. When we use our computers and connect to the network or use web services, we trust that our personal and sensitive information (images, passwords, credit card number ...etc) are confidential and well secured by the used security system. Unfortunately, the hackers may succeed to gain access to the system and... Today the security aspect is a backbone of every computer system, particularly when this system contains sensitive information. When we use our computers and connect to the network or use web services, we trust that our personal and sensitive information (images, passwords, credit card number ...etc) are confidential and well secured by the used security system. Unfortunately, the hackers may succeed to gain access to the system and misuse our information. Generally, the aim of the intrusion is to find new ways to annoy, steal and harm parts of computer systems. Moreover, with the possibility of connecting several computers and networks, the necessity of protecting the whole data and machines from attackers (hackers) that try to get some confident information to use for their own benefit or just destroy or modify valuable information was born. At this point IDS appears to help users, companies or institutions to detect when they are getting compromised. In this paper, we develop an intrusion detection system using multi agent system, ontological techniques (IDSMAO) and misuse method. Read More Read Less

Abstract In recent years, Automatic Natural Language Processing (ANLP) for Arabic language has received a great amount of attention for the development of several applications such as question answering, information retrieval and translation, etc. However, there are a few automated applications using Semantic Web technologies for retrieving Arabic-language documents despite the high demand and need for this content. In addition, the Arabic language presents serious challenges to researchers and developers... In recent years, Automatic Natural Language Processing (ANLP) for Arabic language has received a great amount of attention for the development of several applications such as question answering, information retrieval and translation, etc. However, there are a few automated applications using Semantic Web technologies for retrieving Arabic-language documents despite the high demand and need for this content. In addition, the Arabic language presents serious challenges to researchers and developers of NLP applications. These challenges are due to the complexity of the morphological, syntactic and semantic characteristics specific to the Arabic text, which requires the use of semantic resources such as ontology. In our work, we propose a new approach based on ontology and multi-agent systems to index and filter Arabic documents. Our proposal is composed of five layers, each layer contains several agents: (1) Lexical Layer; (2) Syntactic Layer; (3) Semantic Layer; (4) Indexing Layer; and GUI/Interface Layer. Our Arabic ontology is manually constructed on the basis of schemes and their semantics meanings. We use also combination of Arabic WordNet contents and Arabic VerbNet in the process of constructing the ontology. We use the semantic similarity to find the relevant documents according to the users queries. The aim of this paper is to study the effect of patterns in solving the problem of the semantic indexing system (SIS). The main objective is to improve the quality of the indexing process to ensure the accuracy of the information search of relevant documents based on us ers multiword queries, and also to reduce indexing and search time. Indeed, our experiments are conducted on the basis of the combination of two Arab corpus: OSAC and SemEval. We compared our results Ontological Approach Based on Multi-Agent System for Indexing and Filtering Arabic Documents with Lucene in- dex for the same data and, we found that our approach achieves much better results than the other. Read More Read Less