arXiv subjects

Thabet Slimani

Publications and source records attributed to Thabet Slimani.

11 recordsLinked to original sources

arXiv2015

A Study Investigating Typical Concepts and Guidelines for Ontology Building

In semantic technologies, the shared common understanding of the structure of information among artifacts (people or software agents) can be realized by building an ontology. To do this, it is imperative for an ontology builder to answer several questions: a) what are the main components of an ontology? b) How an ontology look likes and how it works? c) Verify if it is required to consider reusing existing ontologies or not? c) What is the complexity of the ontology to be developed? d) What are the principles of ontology design and development? e) How to evaluate an ontology? This paper answers all the key questions above. The aim of this paper is to present a set of guiding principles to help ontology developers and also inexperienced users to answer such questions.

cs.AI↗

arXiv2015

Class Association Rules Mining based Rough Set Method

This paper investigates the mining of class association rules with rough set approach. In data mining, an association occurs between two set of elements when one element set happen together with another. A class association rule set (CARs) is a subset of association rules with classes specified as their consequences. We present an efficient algorithm for mining the finest class rule set inspired form Apriori algorithm, where the support and confidence are computed based on the elementary set of lower approximation included in the property of rough set theory. Our proposed approach has been shown very effective, where the rough set approach for class association discovery is much simpler than the classic association method.

cs.DB↗

arXiv2014

Efficient Analysis of Pattern and Association Rule Mining Approaches

The process of data mining produces various patterns from a given data source. The most recognized data mining tasks are the process of discovering frequent itemsets, frequent sequential patterns, frequent sequential rules and frequent association rules. Numerous efficient algorithms have been proposed to do the above processes. Frequent pattern mining has been a focused topic in data mining research with a good number of references in literature and for that reason an important progress has been made, varying from performant algorithms for frequent itemset mining in transaction databases to complex algorithms, such as sequential pattern mining, structured pattern mining, correlation mining. Association Rule mining (ARM) is one of the utmost current data mining techniques designed to group objects together from large databases aiming to extract the interesting correlation and relation among huge amount of data. In this article, we provide a brief review and analysis of the current status of frequent pattern mining and discuss some promising research directions. Additionally, this paper includes a comparative study between the performance of the described approaches.

cs.DB↗

arXiv2013

New Approach to Optimize the Time of Association Rules Extraction

The knowledge discovery algorithms have become ineffective at the abundance of data and the need for fast algorithms or optimizing methods is required. To address this limitation, the objective of this work is to adapt a new method for optimizing the time of association rules extractions from large databases. Indeed, given a relational database (one relation) represented as a set of tuples, also called set of attributes, we transform the original database as a binary table (Bitmap table) containing binary numbers. Then, we use this Bitmap table to construct a data structure called Peano Tree stored as a binary file on which we apply a new algorithm called BF-ARM (extension of the well known Apriori algorithm). Since the database is loaded into a binary file, our proposed algorithm will traverse this file, and the processes of association rules extractions will be based on the file stored on disk. The BF-ARM algorithm is implemented and compared with Apriori, Apriori+ and RS-Rules+ algorithms. The evaluation process is based on three benchmarks (Mushroom, Car Evaluation and Adult). Our preliminary experimental results showed that our algorithm produces association rules with a minimum time compared to other algorithms.

cs.DB↗

arXiv2013

Semantic Annotation: The Mainstay of Semantic Web

Given that semantic Web realization is based on the critical mass of metadata accessibility and the representation of data with formal knowledge, it needs to generate metadata that is specific, easy to understand and well-defined. However, semantic annotation of the web documents is the successful way to make the Semantic Web vision a reality. This paper introduces the Semantic Web and its vision (stack layers) with regard to some concept definitions that helps the understanding of semantic annotation. Additionally, this paper introduces the semantic annotation categories, tools, domains and models.

cs.DL↗

arXiv2013

Deployment of VoIP Technology: QoS Concerns

Voice over IP (VoIP) is an emerging communication service allowing voice transmission over a private or a public IP network. VoIP allows significant benefits for customers and service providers including cost savings, phone and service portability, mobility, and the integration with other applications. Nevertheless, the deployment of the VoIP technology encounters many challenges such as interoperability issues, security issues, and QoS concerns. Among these disadvantages, QoS issues are considered the most serious due to the QoS problems that may arise on IP networks, and the stringent QoS requirements of voice traffic. The aim of this paper is carry out a deep analysis of the QoS concerns of the VoIP technology. Firstly, we present a brief overview about the VoIP technology. Then, we discuss the QoS issues related to the use of the IP networking technology for voice traffic transmission. After that, we present the QoS concerns related voice clarity. Finally, we present the QoS mechanisms proposed to make the IP technology able to support voice traffic QoS requirements in terms of voice clarity, voice packet delay, packet delay variation, and packet loss.

cs.NI↗

arXiv2013

Application of Rough Set Theory in Data Mining

Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision making. Data mining is a discipline that has an important contribution to data analysis, discovery of new meaningful knowledge, and autonomous decision making. The rough set theory offers a viable approach for decision rule extraction from data.This paper, introduces the fundamental concepts of rough set theory and other aspects of data mining, a discussion of data representation with rough set theory including pairs of attribute-value blocks, information tables reducts, indiscernibility relation and decision tables. Additionally, the rough set approach to lower and upper approximations and certain possible rule sets concepts are introduced. Finally, some description about applications of the data mining system with rough set theory is included.

cs.DB↗

arXiv2013

Sequential Mining: Patterns and Algorithms Analysis

This paper presents and analysis the common existing sequential pattern mining algorithms. It presents a classifying study of sequential pattern-mining algorithms into five extensive classes. First, on the basis of Apriori-based algorithm, second on Breadth First Search-based strategy, third on Depth First Search strategy, fourth on sequential closed-pattern algorithm and five on the basis of incremental pattern mining algorithms. At the end, a comparative analysis is done on the basis of important key features supported by various algorithms. This study gives an enhancement in the understanding of the approaches of sequential pattern mining.

cs.DB↗

arXiv2013

Description and Evaluation of Semantic Similarity Measures Approaches

In recent years, semantic similarity measure has a great interest in Semantic Web and Natural Language Processing (NLP). Several similarity measures have been developed, being given the existence of a structured knowledge representation offered by ontologies and corpus which enable semantic interpretation of terms. Semantic similarity measures compute the similarity between concepts/terms included in knowledge sources in order to perform estimations. This paper discusses the existing semantic similarity methods based on structure, information content and feature approaches. Additionally, we present a critical evaluation of several categories of semantic similarity approaches based on two standard benchmarks. The aim of this paper is to give an efficient evaluation of all these measures which help researcher and practitioners to select the measure that best fit for their requirements.

cs.CL↗

arXiv2013

Semantic Description of Web Services

The tasks of semantic web service (discovery, selection, composition, and execution) are supposed to enable seamless interoperation between systems, whereby human intervention is kept at a minimum. In the field of Web service description research, the exploitation of descriptions of services through semantics is a better support for the life-cycle of Web services. The large number of developed ontologies, languages of representations, and integrated frameworks supporting the discovery, composition and invocation of services is a good indicator that research in the field of Semantic Web Services (SWS) has been considerably active. We provide in this paper a detailed classification of the approaches and solutions, indicating their core characteristics and objectives required and provide indicators for the interested reader to follow up further insights and details about these solutions and related software.

cs.AI↗

arXiv2013

IAX-Based Peer-to-Peer VoIP Architecture

Nowadays, Voice over IP (VoIP) constitutes a privileged field of service innovation. One benefit of the VoIP technology is that it may be deployed using a centralized or a distributed architecture. One of the most efficient approaches used in the deployment of centralized VoIP systems is based on the use of IAX (Inter-Asterisk Exchange), an open-source signaling/data exchange protocol. Even though they are currently widely used, client-server VoIP systems suffer from many weaknesses such as the presence of single points of failure, an inefficient resources management, and system non-scalability. In order to help the development of scalable and reliable VoIP systems, the development community starts tending towards the deployment of the VoIP service using a peer-to-peer distributed architecture. The aim of this paper is to develop an IAX-based peer-to-peer VoIP architecture, an optimized VoIP architecture that takes advantage of the benefits of the IAX protocol and those of the peer-to-peer distribution model.

cs.NI↗