Malek Mouhoub

Malek Mouhoub
University of Regina · Department of Computer Sciences

PhD

About

176
Publications
67,999
Reads
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763
Citations
Introduction
Artificial Intelligence, Combinatorial Optimization, Constraint Satisfaction, Geographic Information Systems (GIS) Machine Learning, Metaheuristics, Natural Language Processing, Preference Reasoning, Robot Motion Planning, Scheduling, Planning and Timetabling, Spatio-Temporal Reasoning.
Additional affiliations
July 2009 - present
University of Regina
Position
  • Professor
July 2009 - present
University of Regina
Position
  • Professor (Full)
July 2002 - June 2009
University of Regina
Position
  • Professor (Associate)

Publications

Publications (176)
Article
Full-text available
Learning of user preferences, as represented by, for example, Conditional Preference Networks (CP-nets), has become a core issue in AI research. Recent studies investigate learning of CP-nets from randomly chosen examples or from membership and equivalence queries. To assess the optimality of learning algorithms as well as to better understand the...
Article
User's choices involve habitual behavior and genuine decision. Habitual behavior is often expressed using preferences. In a multiattribute case, the Conditional Preference Network (CP‐net) is a graphical model to represent user's conditional ceteris paribus (all else being equal) preference statements. Indeed, the CP‐net induces a strict partial or...
Article
We are witnessing an increasing proliferation of hate speech on social media targeting individuals for their protected characteristics. Our study aims to devise an effective Arabic hate and offensive speech detection framework to address this serious issue. First, we built a reliable Arabic textual corpus by crawling data from Twitter using four ro...
Article
Full-text available
Graph Coloring Problems (GCPs) are constraint optimization problems with various applications including time tabling and frequency allocation. The GCP consists in finding the minimum number of colors for coloring the graph vertices such that adjacent vertices have distinct colors. We propose a hierarchical approach based on Parallel Genetic Algorit...
Article
Full-text available
A Conditional Preferences network (CP-net) is a known graphical model for representing qualitative preferences. In many real world applications we are often required to manage both constraints and preferences in an efficient way. The goal here is to select one or more scenarios that are feasible according to the constraints while maximizing a given...
Article
Full-text available
Combinatorial applications such as configuration, transportation and resource allocation often operate under highly dynamic and unpredictable environments. In this regard, one of the main challenges is to maintain a consistent solution anytime constraints are (dynamically) added. While many solvers have been developed to tackle these applications,...
Conference Paper
The Conditional Preference Network (CP-net) is one of the widely used graphical models for representing and reasoning with qualitative preferences under ceteris paribus ("all else being equal") assumptions. CP-nets have been extended to Constrained CP-nets (CCP-nets) in order to consider constraints between attributes. Adding constraints will restr...
Conference Paper
Full-text available
This study aims to improve disease detection accuracy by incorporating a discrete version of the Whale Optimization Algorithm (WOA) into a supervised classification framework (KNN). We devise the discrete WOA by redefining the related components to operate on discrete spaces. More precisely, we redefine the notion of distance (between individuals i...
Conference Paper
Analysing the sentiments in online reviews assists in understanding customers’ satisfaction with a provided service or product, which gives the industry an opportunity to enhance the quality of their commodity, increase sales volume, develop marketing strategies, improve response to customers, promote customer satisfaction, and enhance the industry...
Chapter
The Nurse Scheduling Problem (NSP) is one of the challenging combinatorial optimization problems encountered in the healthcare sector. Solving the NSP consists in building weekly schedules by assigning nurses to shift patterns, such that workload constraints are satisfied, while nurses’ preferences are maximized. In addition to the difficulty to ta...
Conference Paper
There are limited research contributions targeting sentiment analysis in feedback in Arabic gulf dialect, in particular, and the Arabic language in general. Furthermore, the inadequate and limited adoption of classification techniques and natural language processing is noticeable in the sentiment analysis projects addressing the Arabic language. He...
Conference Paper
A Conditional Preference Network (CP-net) is a graphical model widely used to represent qualitative preferences in many real-world applications. Preference elicitation, representation , and reasoning plays an essential role in e-commerce and other applications relying on users' preferences and desires. However, managing preferences often comes with...
Preprint
Full-text available
The Conditional Preference Network (CP-net) graphically represents user's qualitative and conditional preference statements under the ceteris paribus interpretation. The constrained CP-net is an extension of the CP-net, to a set of constraints. The existing algorithms for solving the constrained CP-net require the expensive dominance testing operat...
Preprint
Full-text available
A Qualitative Constraint Network (QCN) is a constraint graph for representing problems under qualitative temporal and spatial relations, among others. More formally, a QCN includes a set of entities, and a list of qualitative constraints defining the possible scenarios between these entities. These latter constraints are expressed as disjunctions o...
Preprint
Full-text available
We propose an Ontology-Based Information Extraction (OBIE) system to automate the extraction of the criteria and values applied in Land Use Suitability Analysis (LUSA) from bylaw and regulation documents related to the geographic area of interest. The results obtained by our proposed LUSA OBIE system (land use suitability criteria and their values)...
Article
Full-text available
Optimization and its related solving methods are becoming increasingly important in most academic and industrial fields. The goal of the optimization process is to make a system or a design as effective and functional as possible. This is achieved by optimizing a set of objectives while meeting the system requirements. Optimization techniques are c...
Conference Paper
Full-text available
The development of a communication aid tool for Non-English-Speaking newcomers to Canada is very important for their integration, self-reliance, and contribution to the new society. Such a tool will indeed overcome the language barriers that the newcomers might be challenged with, which will ease their struggle in their first days in a foreign coun...
Preprint
Full-text available
Combinatorial applications such as configuration, transportation and resource allocation, often operate under highly dynamic and unpredictable environments. In this regard, one of the main challenges is to maintain a consistent solution anytime constraints are (dynamically) added. While many solvers have been developed to tackle these applications,...
Conference Paper
Full-text available
Mobile devices are used by numerous applications that continuously need computing power to grow. Due to limited resources for complex computing, offloading, a service offered for mobile devices, is commonly used in cloud computing. In Mobile Cloud Computing (MCC), offloading decides where to execute the tasks to efficiently maximize the benefits. H...
Preprint
Full-text available
This study aims to optimize Deep Feedforward Neural Networks (DFNNs) training using nature-inspired optimization algorithms, such as PSO, MTO, and its variant called MTOCL. We show how these algorithms efficiently update the weights of DFNNs when learning from data. We evaluate the performance of DFNN fused with optimization algorithms using three...
Book
https://www.inderscience.com/info/inarticletoc.php?jcode=ijdmmm&year=2021&vol=13&issue=1/2
Preprint
Full-text available
This research work is intended to assess the usability of Pictogram symbols and other visual symbols in an audio-visual strategy to facilitate and enhance the use and learning of English as an additional language for Arabic-speaking Syrian refugees, with a potential for generalizing the process to speakers from other linguistic backgrounds. The ado...
Conference Paper
Temporal and spatial reasoning is a fundamental task in artificial intelligence and its related areas including scheduling, planning and Geographic Information Systems (GIS). In these applications, we often deal with incomplete and qualitative information. In this regard, the symbolic representation of time and space using Qualitative Constraint Ne...
Preprint
Full-text available
Deep neural networks have been adopted successfully in hate speech detection problems. Nevertheless, the effect of the word embedding models on the neural network's performance has not been appropriately examined in the literature. In our study, through different detection tasks, 2-class, 3-class, and 6-class classification, we investigate the impa...
Conference Paper
The Mother Tree Optimization (MTO) algorithm is a new swarm intelligence technique that we have recently proposed for solving continuous optimization problems. MTO is built on an offspring topol-ogy and a set of cooperating agents. In this paper, we first present a discrete version of MTO, that we call Discrete MTO (DMTO), for solving the Traveling...
Conference Paper
Full-text available
Our study explores offensive and hate speech detection for the Arabic language, as previous studies are minimal. Based on two-class, three-class, and six-class Arabic-Twitter datasets, we develop single and ensemble CNN and BiLSTM classifiers that we train with non-contextual (Fasttext-SkipGram) and contextual (Multilingual Bert and AraBert) word-e...
Conference Paper
The studies addressing the application of machine and deep learning models to analyze the sentiments of Arabic online reviews related to the real-estate and automobile fields are not mature. To fill this gap, this research has focused on classifying three types of sentiments in Arabic real-estate and automobile online reviews, which are negative, p...
Conference Paper
Full-text available
A significant amount of water, energy and time are often wasted, before someone gets the desired water temperature in a bathroom or a kitchen. In this paper, we propose a novel electro-mechanical device for mixing the water intelligently, which is effective for saving water, energy and time. The problem that we intend to solve can be seen as a mult...
Article
Full-text available
Constraint optimization consists of looking for an optimal solution maximizing a given objective function while meeting a set of constraints. In this study, we propose a new algorithm based on mushroom reproduction for solving constraint optimization problems. Our algorithm, that we call Mushroom Reproduction Optimization (MRO), is inspired by the...
Chapter
The online retail industry has changed the way customers shop as everything is available online. In order to build a loyal customer base, a company needs to deploy various marketing strategies focused on the diverse nature of its customers. We propose a model, abbreviated as RFMOC, based on extension of recency frequency, monetary (RFM) analysis wi...
Conference Paper
Full-text available
We present a new nature-inspired approach based on the Focus Group Optimization Algorithm (FGOA) for solving Constraint Satisfaction Problems (CSPs). CSPs are NP-complete problems meaning that solving them by classical systematic search methods requires exponential time, in theory. Appropriate alternatives are approximation methods such as metaheur...
Chapter
Automatic diagnostic tools have been extensively implemented in medical diagnosis processes of different diseases. In this regard, breast cancer diagnosis is particularly important as it becomes one of the most dangerous diseases for women. Consequently, regular and preemptive screening for breast cancer could help initiate treatment earlier and mo...
Conference Paper
Full-text available
We present a new nature-inspired approach based on the Focus Group Optimization Algorithm (FGOA) for solving Constraint Satisfaction Problems (CSPs). CSPs are NP-complete problems meaning that solving them by classical systematic search methods requires exponential time, in theory. Appropriate alternatives are approximation methods such as metaheur...
Conference Paper
We present a new nature-inspired approach based on the Focus Group Optimization Algorithm (FGOA) for solving Constraint Satisfaction Problems (CSPs). CSPs are NP-complete problems meaning that solving them by classical systematic search methods requires exponential time, in theory. Appropriate alternatives are approximation methods such as metaheur...
Conference Paper
Full-text available
Constraint Satisfaction Problems (CSPs) provide an appropriate framework to formulate many real-world applications including scheduling, planning and resource allocation. However, the CSP description can change due to the evolving environment. The latter points to the fact that constraints might be subject to change over time and this can affect th...
Conference Paper
Full-text available
A Weighted Constraint Satisfaction Problem (WCSP) is a Constraint Satisfaction Problem in which preferences between solutions are considered, meaning that some solutions are more preferred than others and the optimal solution is the one with minimum weight. Such problems are usually dealt with classical complete methods like bucket elimination tech...
Conference Paper
Full-text available
Constraint Solving and Optimization is very relevant in many real world applications including scheduling, planning, configuration, resource allocation and timetabling. Solving a constraint optimization problem consists of finding an assignment of values to variables that optimizes some defined objective functions, subject to a set of constraints i...
Conference Paper
Full-text available
Many real-world problems such as scheduling, planning and resource allocation can be represented and solved as Constraint Satisfaction Problems (CSPs). The main challenge when tackling these applications is the fact that they occur in an evolving environment. That is, constraints might change over time and this can affect the feasibility of the sol...
Chapter
A Conditional Preference Network with Comfort (CPC-net) graphically represents both preference and comfort. Preference and comfort indicate user’s habitual behavior and genuine decisions correspondingly. Given that these two concepts might be conflicting, we find it necessary to introduce Pareto optimality when achieving outcome optimization with r...
Chapter
The CP-net and the LP-tree are two fundamental graphical models for representing user’s qualitative preferences. Constrained CP-nets have been studied in the past in which a very expensive operation, called dominance testing, between outcomes is required. In this paper, we propose a recursive backtrack search algorithm that we call Search-LP to fin...
Conference Paper
Full-text available
This paper presents a new Chaotic Discrete Firefly Algorithm (CDFA) for solving Constraint Satisfaction Problems (CSPs). CSPs are known as NP-complete problems requiring systematic search methods of exponential time costs for solving them. Metaheuristic algorithms that have been developed for solving complex problems can be considered as appropriat...
Article
Full-text available
The 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE-2018) was held at Concordia University in Montreal, Canada, June 25–28, 2018. This report summarizes the The 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/A...
Conference Paper
Full-text available
Online auctions created a very attractive environment for dishonest moneymakers who can commit different types of fraud. Shill Bidding (SB) is the most predominant auction fraud and also the most difficult to detect because of its similarity to usual bidding behavior. Based on a newly produced SB dataset, in this study, we devise a fraud classifica...
Article
Full-text available
Topic modeling is a powerful technique for unsupervised analysis of large document collections. Topic models have a wide range of applications including tag recommendation, text categorization, keyword extraction and similarity search in the text mining, information retrieval and statistical language modeling. The research on topic modeling is gain...
Article
Full-text available
TCP-nets are graphical tools for modeling user's preference and relative importance statements. We propose the Prob-abilistic TCP-net (PTCP-net) model that can aggregate a set of TCP-nets, in a compact form, sharing the same set of variables and their domains but having different preference and relative importance statements. In particular, the PTCP...
Conference Paper
Full-text available
We introduce a new nature-inspired optimization algorithm namely Mushroom Reproduction Optimization (MRO) inspired and motivated by the reproduction and growth mechanisms of mushrooms in nature. MRO follows the process of discovering rich areas (containing good living conditions) by spores to grow and develop their own colonies. We thoroughly asses...
Article
Full-text available
A Constraint Satisfaction Problem (CSP) is a very powerful framework for representing and solving constraint problems. Solving a CSP often requires searching for a solution in a large search space. Very often, much of the search efforts are wasted on the part of the search space that does not lead to a solution. Therefore, many search algorithms an...
Conference Paper
Full-text available
Constraint Satisfaction Problems are regarded as NP-Complete problems which solving them with systematic methods requires exponential time. Firefly algorithm is a nature inspired algorithm which has been successfully applied to different combinatorial problems. This paper presents a new Discrete Firefly Algorithm for Solving Constraint Satisfaction...
Book
This book constitutes the refereed proceedings of the 6th IFIP TC 5 International Conference on Computational Intelligence and Its Applications, CIIA 2018, held in Oran, Algeria, in May 2018. The 56 full papers presented were carefully reviewed and selected from 202 submissions. They are organized in the following topical sections: data mining and...
Conference Paper
Full-text available
Constraints Satisfaction Problems (CSPs) are known to be hard to solve and require a backtrack search algorithm with exponential time cost. Metaheuristics have recently gained much reputation for solving complex problems and can be employed as an alternative to tackle CSPs even if, in theory, they do not guarantee a complete solution to the problem...
Article
Full-text available
Learning of user preferences, as represented by, for example, Conditional Preference Networks (CP-nets), has become a core issue in AI research. Recent studies investigate learning of CP-nets from randomly chosen examples or from membership and equivalence queries. To assess the optimality of learning algorithms as well as to better understand the...
Article
Full-text available
Exploitation and exploration are two main search strategies of every metaheuristic algorithm. However, the ratio between exploitation and exploration has a significant impact on the performance of these algorithms when dealing with optimization problems. In this study, we introduce an entire fuzzy system to tune efficiently and dynamically the fire...
Article
Full-text available
Exploitation and exploration are two main search strategies of every metaheuristic algorithm. However, the ratio between exploitation and exploration has a significant impact on the performance of these algorithms when dealing with optimization problems. In this study, we introduce an entire fuzzy system to tune efficiently and dynamically the fir...
Book
This book constitutes the thoroughly refereed proceedings of the 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, held in Montreal, QC, Canada, in June 2018. The 53 full papers and 33 short papers presented were carefully reviewed and selected from 146 submissions. They ar...
Article
Full-text available
Cities are complex spatial systems and modeling their dynamics of growth using traditional modeling techniques is a challenging task. Cellular automata (CA) have been widely used for modeling urban growth because of their computational simplicity, their explicit representation of time and space and their ability to generate complex patterns from th...
Conference Paper
Full-text available
Exploration and exploitation are two strategies used to search the problem space in Evolutionary Algorithms (EAs). To significantly increase the performance of these optimization techniques in terms of the solution optimality is to strike the right balance between exploration and exploitation. Firefly is one of the most favored EAs. In this study,...
Conference Paper
The Shortest Route Problem concerns routing one vehicle to one customer while minimizing some objective functions. The problem is essentially a shortest path problem and has been studied extensively in the literature. We report a system with the objective to address two dynamic aspects of the Shortest Route Problem. The first aspect corresponds to...
Conference Paper
TCP-nets are graphical tools for modeling user’s preference and relative importance statements. We propose the Probabilistic TCP-net (PTCP-net) model that can represent a set of TCP-nets, in a compact form, sharing the same set of variables and their domains but having different preference and relative importance statements. In particular, the PTCP...
Conference Paper
A Constraint Satisfaction Problem (CSP) is a powerful formalism to represent constrained problems. A CSP includes a set of variables where each is defined over a set of possible values, and a set of relations restricting the values that the variables can simultaneously take. There are numerous problems that can be represented as CSPs. Solving CSPs...