This special issue of the Journal of Data Semantics includes the extended versions of five select... more This special issue of the Journal of Data Semantics includes the extended versions of five selected papers from the fifth French-Speaking Conference on Ontologies (Journées Francophones sur les Ontologies), which took place from November 14-16, 2014, in Hammamet, Tunisia. The papers were selected by taking into account the quality, significance and relevance of the results they present. All the extended papers went through an additional peer review process. The first paper "Ontologies-Based Platform for Sociocultural Knowledge Management" by Papa Fary Diallo, Olivier Corby, Isabelle Mirbel, Moussa Lo and Seydina Ndiaye, presents a sociocultural platform aiming at persevering and capitalizing sociocultural events in Senegal. This platform relies on Semantic Web technologies. Authors discuss the two ontologies that they provided to support their platform: an upper-level sociocultural ontology (USCO) and a human time ontology (HuTO). To build the upper-level ontology, authors proposed a methodology based on the theory of Russian psychologist Lev Vygotsky called "Vygotskian Framework". They also present how this ontology can be matched in the Linked Open Data (LOD) cloud. On the other hand, they present the second ontology: HuTO, of which major contributions are (1) the modeling of nonconvex intervals (repetitive interval) like every Monday, (2) representation of deictic temporal expressions which form specific relations with time speech and (3) qualitative temporal notions which are temporal notions relative to a culture or a geographical position. Finally, the paper presents and discusses the platform designed on top of Semantic Medi-aWiki (SMW) to apply the authors' scientific contributions.
International Journal of Hybrid Intelligent Systems, Nov 26, 2021
Since December 2019, we have detected the appearance of a new virus called COVID-19, which has sp... more Since December 2019, we have detected the appearance of a new virus called COVID-19, which has spread, throughout the world. Everyone today, has given major importance to this new virus. Although we have little knowledge of the disease, doctors and specialists make decisions every day that have a significant impact on public health. There are many and various open data in this context, which are scattered and distributed. For this, we need to capitalize all the information in a data warehouse. For that, in this paper, we propose an approach to create a data warehouse from open data specifically from COVID-19 data. We start with the identification of the relevant sources from the various open data. Then, we collect the pertinent data. After that, we identify the multidimensional concepts used to design the data warehouse schema related to COVID-19 data. Finally, we transform our data warehouse to logical model and create our NoSQL data warehouse with Talend Open Studio for Big Data (TOS_BD).
This paper presents our first participation in user-centred health information retrieval task at ... more This paper presents our first participation in user-centred health information retrieval task at the CLEFeHealth 2014. This task has as objective the information retrieval to answer patients' questions when reading clinical reports. We have submitted only the mandatory run (baseline system). The obtained results are motivating with map=0.1677 and p@10=0.5460 but can be improved.
Providing a customized support for the OLAP brings tremendous challenges to the OLAP technology. ... more Providing a customized support for the OLAP brings tremendous challenges to the OLAP technology. Standing at the crossroads of the preferences and the data warehouse, two emerging trends are pointed out; namely: (i) the personalization and (ii) the recommendation. Although the panoply of the proposed approaches, the user-centric data warehouse community issues have not been addressed yet. In this paper we draw an overview of several user centric data warehouse proposals. We also discuss the two promising concepts in this issue, namely, the personalization and the recommendation of the data warehouses. We compare the current approaches among each others with respect to some criteria.
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference, May 4, 2022
In this paper, we place ourselves in the context of inconsistency-tolerant query answering over l... more In this paper, we place ourselves in the context of inconsistency-tolerant query answering over lightweight ontologies, which aims to query a set of conflicting facts using an ontology that represents generic knowledge about a particular domain. Existing inconsistency-tolerant semantics typically consist in selecting some of (maximal) consistent subsets of facts, called repairs. We explore a novel strategy to select the most relevant repairs based on the stratification of the assertional base into priority levels that we automatically induce from the ontology. We propose a method that exploits conflict statistical regularities between facts to induce an embedding, in which each fact is represented by a vector. Based on Euclidean distances between facts, we classify the assertions from the most reliable to the least important ones. We then use these distances to define relevant repairs. Interestingly enough, we show that the obtained repair is done in polynomial time.
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference, May 4, 2022
The EL is a tractable family of lightweight description logics that underlay the OWL EL profile. ... more The EL is a tractable family of lightweight description logics that underlay the OWL EL profile. It guarantees the tractability of the reasoning process, especially for concept classification. In particular, such a fragment is widely used for medical applications. This paper investigates the evolution of EL ontologies when a new piece of information that can be conflicting or attached with a confidence level reflecting its credibility or priority is available. To encode such knowledge, we propose an extension of EL description logic within the possibility theory, which provides a natural way to deal with ordinal scale reflecting ranking between pieces of knowledge. We then show how such a ranking between axioms is induced from the ontology with the presence of new information and study the evolution process at the semantic level. Finally, we propose a polynomial syntactic counterpart of the evolution process while preserving the consistency of the ontology.
Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2019
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific r... more HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
International Journal of Web-Based Learning and Teaching Technologies, 2021
Nowadays, the virtual learning environment has become an ideal tool for professional self-develop... more Nowadays, the virtual learning environment has become an ideal tool for professional self-development and bringing courses for various learner audiences across the world. There is currently an increasing interest in researching the topic of learner dropout and low completion in distance learning, with one of the main concerns being elevated rates of occurrence. Therefore, the early prediction of learner withdrawal has become a major challenge, as well as identifying the factors, which contribute to this increasingly occurring phenomenon. In that regard, this manuscript presents a framework for withdrawal prediction model for the data from The Open University, one of the largest distance learning institutions. For that purpose, we start by pre-processing the dataset and tackling the challenge of discretization process and unbalanced data. Secondly, this paper identifies the semantical issues of raw data by introducing new behavioural indicators. Finally, we reckon on machine learning...
Ontology matching is an effective strategy to find the correspondences among different ontologies... more Ontology matching is an effective strategy to find the correspondences among different ontologies in a scalable and heterogeneous semantic web. In order to find these correspondences, a matching system should be built aiming to ensure the interoperability between the aligned entities. POMap (Pairwise Ontology Mapping) is an automated ontology matching system dealing with the three main types of heterogeneity: syntactic, semantic and structural. During our first participation in the OAEI campaign, POMap succeeded to be one of the top three performing systems in the Anatomy track. In the remaining of this paper, we briefly introduce POMap and discuss its OAEI 2017 results according to four tracks: Anatomy, Conference, Large Biomedical Ontoloies, Disease and Phenotype.
POMap++ is a novel ontology matching system based on a machine learning approach. This year is th... more POMap++ is a novel ontology matching system based on a machine learning approach. This year is the second participation of POMap++ in the Ontology Alignment Evaluation Initiative (OAEI). POMap++ follows a fully automated local matching learning approach that breaks down a large ontology matching task into a set of independent local sub-matching tasks. This approach integrates a novel partitioning algorithm as well as a set of matching learning techniques. POMap++ provides an automated local matching learning for the biomedical tracks. In this paper, we present POMap++ as well as the obtained results for the Ontology Alignment Evaluation Initiative of 2019.
Wildfire prediction from Earth Observation (EO) data has gained much attention in the past years,... more Wildfire prediction from Earth Observation (EO) data has gained much attention in the past years, through the development of connected sensors and weather satellites. Nowadays, it is possible to extract knowledge from collected EO data and to learn from this knowledge without human intervention to trigger wildfire alerts. However, exploiting knowledge extracted from multiple EO data sources at run-time and predicting wildfire raise multiple challenges. One major challenge is to provide dynamic construction of service composition plans, according to the data obtained from sensors. In this paper, we present a knowledgedriven Machine Learning approach that relies on historical data related to wildfire observations to guide the collection of EO data and to automatically and dynamically compose services for triggering wildfire alerts.
Data mining has emerged to address the problem of drawing interesting knowledge from data. Among ... more Data mining has emerged to address the problem of drawing interesting knowledge from data. Among the most used data mining techniques, we concentrate on association rules which lead to the derivation of useful associations and correlations within data. In parallel, the advance of the ontology which is one of the most important concepts in knowl- edge representation has speedily altered the way of information structuring and sharing. Recently, the area of coupling association rules and ontology has been a focus for several researchers. In this paper, we aim to extract enhanced association rules over ontological resource. Thus, we introduce a new approach ECARD for an enhanced association rules derivation. Indeed, two main categories of knowledge are drawn, namely transitive and causal association rules. The encouraging carried out experimental results show the usefulness of our approach.
International Journal of Information System Modeling and Design, 2019
The development of information systems (IS) in a secure environment or condition is a complex tas... more The development of information systems (IS) in a secure environment or condition is a complex task that involves many additional basic security protocols, policies as well as industry standards on passwords, anti-virus programs, firewalls and data encryption. However, in traditional IS development lifecycles, security is either ignored or added as an afterthought, which does not assure the system complete security. So, it is necessary to give more importance to this issue and consider it as part of IS development process. In this context, the authors should guarantee the security of ETL (Extract, Transform, Load) processes, which are among the most critical and complex tasks during DW development project. In this study, security management is carried out for ETL processes by proposing a meta-model integrating the security concepts from the security requirements to the necessary preventive and / or corrective treatments. The proposed meta-model is validated with instantiation.
In the last decade, we have witnessed an explosion of data volume available on the Web. This is d... more In the last decade, we have witnessed an explosion of data volume available on the Web. This is due to the rapid technological advances with the availability of smart devices and social networks such as Twitter, Facebook, Instagram, etc. Hence, the concept of Big Data was created to face this constant increase. In this context, many domains should take in consideration this growth of data, especially, the Business Intelligence (BI) domain. Where, it is full of important knowledge that is crucial for effective decision making. However, new problems and challenges have appeared for the Decision Support System that must be addressed. Accordingly, the purpose of this paper is to adapt Extract-Transform-Load (ETL) processes with Big Data technologies, in order to support decision-making and knowledge discovery. In this paper, we propose a new approach called Big Dimensional ETL (BigDimETL) dealing with ETL development process and taking into account the Multidimensional structure. In addition, in order to accelerate data handling we used the MapReduce paradigm and Hbase as a distributed storage mechanism that provides data warehousing capabilities. Experimental results show that our ETL operation adaptation can perform well especially with Join operation.
Advances in Intelligent Systems and Computing, 2017
With the broad range of data available on the World Wide Web and the increasing use of social med... more With the broad range of data available on the World Wide Web and the increasing use of social media such as Facebook, Twitter, YouTube, etc. a "Big Data" notion has emerged. This latter has become an important aspect in nowadays business since it is full of important knowledge that is crucial for effective decision making. However, this kind of data brings with it new problems and challenges for the decisional support system (DSS) that must be addressed. In this paper, we propose a new approach called BigDimETL (Big Dimensional ETL) that deals with ETL (Extract-Transform-Load) development. Our approach focus on integrating Big Data taking into account the MultiDimensional Structure (MDS) through MapReduce paradigm.
Proceedings of the 11th International Conference on Web Information Systems and Technologies, 2015
Considered as a rich source of information, social networking sites have been created lot of buzz... more Considered as a rich source of information, social networking sites have been created lot of buzz because people share and discuss their opinions freely. Sentiment analysis is used for knowing voice or response of crowd for products, services, organizations, individuals, events, etc. Due to their importance, people opinions are analyzed in several domains including information retrieval, semantic web, text mining. These researches define new classification techniques to assign positive or negative opinion. Decisional systems like WeBhouse, known by their data-consuming must be enriched by this kind of pertinent opinions to give better help to decision makers. Nevertheless, cleaning and transformation processes recognized by several approaches as a key of WeBhouse development, don't deal with sentiment analysis. To fulfill this gap, we propose a new analysis algorithm which determines user's sentiment score of a post shared on the social network Facebook. This algorithm analyzes user's opinion depending on opinion terms and emoticons included in his comments. This algorithm is integrated in transformation process of ETL approach.
The benefit of locality is one of the major premises of LIME, one of the most prominent methods t... more The benefit of locality is one of the major premises of LIME, one of the most prominent methods to explain black-box machine learning models. This emphasis relies on the postulate that the more locally we look at the vicinity of an instance, the simpler the black-box model becomes, and the more accurately we can mimic it with a linear surrogate. As logical as this seems, our findings suggest that, with the current design of LIME, the surrogate model may degenerate when the explanation is too local, namely, when the bandwidth parameter σ tends to zero. Based on this observation, the contribution of this paper is twofold. Firstly, we study the impact of both the bandwidth and the training vicinity on the fidelity and semantics of LIME explanations. Secondly, and based on our findings, we propose S-LIME, an extension of LIME that reconciles fidelity and locality.
HAL (Le Centre pour la Communication Scientifique Directe), Oct 18, 2006
Contextual ontologies are ontologies that characterize a concept by a set of properties that vary... more Contextual ontologies are ontologies that characterize a concept by a set of properties that vary according to context. Contextual ontologies are now crucial for users who intend to exchange information in a domain. Existing ontology languages are not capable of defining such type of ontologies. The objective of this paper is to formally define a contextual ontology language to support the development of contextual ontologies. In this paper, we use description logics as an ontology language and then we extend it by introducing a new contextual constructor.
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Papers by Faiez Gargouri