@article {ElAkrouchi2021, title = {End-to-end LDA-based automatic weak signal detection in web news}, journal = {Knowledge-Based Systems}, volume = {212}, year = {2021}, note = {cited By 9}, abstract = {An extremely competitive business environment requires every company to monitor its competitors and anticipate future opportunities and risks, creating a dire need for competitive intelligence. In response to this need, foresight study became a prominent field, especially the concept of weak signal detection. This research area has been widely studied for its utility, but it is limited by the need of human expert judgments on these signals. Moreover, the increase in the volume of information on the Internet through blogs and web news has made the detection process difficult, which has created a need for automation. Recent studies have attempted topic modeling techniques, specifically latent Dirichlet allocation (LDA), for automating the weak signal detection process; however, these approaches do not cover all parts of the process. In this study, we propose a fully automatic LDA-based weak signal detection method, consisting of two filtering functions: the weakness function aimed at filtering topics, which potentially contains weak signals, and the potential warning function, which helps to extract only early warning signs from the previously filtered topics. We took this approach with a famous daily web news dataset, and we could detect the risk of the COVID19 pandemic at an early stage. {\textcopyright} 2020 Elsevier B.V.}, keywords = {Competition, Competitive business, Competitive intelligence, Detection process, Early warning signs, Filtering functions, Latent dirichlet allocations, Signal detection, Statistics, Topic Modeling, Weak signal detection, Weak signals}, doi = {10.1016/j.knosys.2020.106650}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097573309\&doi=10.1016\%2fj.knosys.2020.106650\&partnerID=40\&md5=a491fca334a7b047c3a02e16ecb7b3f0}, author = {El Akrouchi, M. and Benbrahim, H. and Kassou, I.} } @conference {ElAkrouchi2021, title = {Review on adopting concept extraction in weak signals detection in competitive intelligence}, booktitle = {ACM International Conference Proceeding Series}, year = {2021}, note = {cited By 0}, abstract = {The dynamic nature of competition in the business environment makes a company{\textquoteright}s ability to secure future change more critical to its survival. Consequently, efficient exploitation of valuable intel is globally acknowledged as an essential foundation of competitive advantage, leading to Competitive Intelligence. Besides, one of the crucial keys to successful competitive information securing is studying the future. Thus, predicting what may happen in the uncertain future is a leading-edge technology leading to an extensive need for foresight analysis. Foresight study uses various methods to recognize future developments and make plans that anticipate possible future changes. One of the leading techniques used in foresight is detecting and understanding Weak Signals. But knowing the nature of these signals, automatically scanning them is still considered a difficult task. For this, we examine the Concept Extraction technique as a main step to detect weak signals from documents automatically. In this paper, we will explain the concept extraction methods used so far, and we present in detail all the main methods and approaches and their application in detecting weak signals. {\textcopyright} 2021 Association for Computing Machinery.}, keywords = {Business environments, Competition, Competitive advantage, Competitive intelligence, Concept extraction, Data mining, Dynamic nature, Extraction, Leading edge technology, Possible futures, Signal detection, Topic Modeling, Weak signal detection, Weak signals}, doi = {10.1145/3485557.3485560}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121505750\&doi=10.1145\%2f3485557.3485560\&partnerID=40\&md5=01161f382ecb38a8faf2883a2bc37003}, author = {El Akrouchi, M. and Benbrahim, H. and Kassou, I.} } @article {Khaouja2021118134, title = {A Survey on Skill Identification from Online Job Ads}, journal = {IEEE Access}, volume = {9}, year = {2021}, note = {cited By 8}, pages = {118134-118153}, abstract = {A changing job market, influenced by different factors such as globalization and demographic growth, urges close monitoring. The digitization of the job market has given the opportunity to researchers to better understand job market needs as job postings/ads become more accessible. However, such postings are submitted in unstructured text and need further processing to identify the required skills. The aim of this survey is to review current research on skill identification from job ads and to discuss possible future research directions. In this study, we systematically reviewed 108 research articles on the topic. In particular, we evaluated and classified the prior work aiming to identify the skill bases used for analyzing job market needs; the type of extracted skills; the skill identification methods; the studied sector and the skill identification granularity. Then, we categorized the existent applications and goals of skill identification. Finally, we present key challenges and discuss recent trends. {\textcopyright} 2013 IEEE.}, keywords = {Commerce, Demographic growth, Employment, Identification method, Job market, Job postings, Possible futures, Recent trends, Surveys, Unstructured texts}, doi = {10.1109/ACCESS.2021.3106120}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113305279\&doi=10.1109\%2fACCESS.2021.3106120\&partnerID=40\&md5=95e3da9f3201c5b0ca744ba8d8af7012}, author = {Khaouja, I. and Kassou, I. and Ghogho, M.} } @conference {ElAkrouchi2020, title = {Monitoring Early Warning Signs Evolution through Time}, booktitle = {ACM International Conference Proceeding Series}, year = {2020}, note = {cited By 0}, abstract = {In excessive business competition, detecting weak signals is very important to anticipate future changes and events. The process of detecting weak signals is very challenging, and many techniques were proposed to automatize this challenge but still needs the intervention of experts{\textquoteright} opinion. Understanding those detected signals and their evolution in time is crucial to reveal the alertness of possible future events and warnings. For this reason, this paper proposes a new algorithm to strengthen weak signals into early warning signs. The proposed algorithm aims to monitor and track weak signals{\textquoteright} evolution within time. The output will be a list of early warning signs and visualization to illustrate their evolution in time. Finally, to adequately understand the early warning signs obtained and enhance their semantic alertness, we used Word2Vec modeling to provide semantically similar words to these warning signs and improve their contextual alertness. We tested this algorithm on a web news dataset of 2006-2007 to detect early warning signs related to the 2008 financial crisis ahead of time. We obtained prominent results in strengthening and monitoring the evolution of early warning signs related to this crisis. {\textcopyright} 2020 ACM.}, keywords = {Artificial intelligence, Business competition, Competition, Early warning signs, Financial crisis, Possible futures, Semantics, Signal detection, Warning signs, Weak signals}, doi = {10.1145/3446132.3446173}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102970850\&doi=10.1145\%2f3446132.3446173\&partnerID=40\&md5=4f35fa04a194332457fca88ff3bec0d1}, author = {El Akrouchi, M. and Benbrahim, H. and Kassou, I.} } @conference {Jeddi20205531, title = {Practical Acoustic Energy-Based Estimation of Inhalation Flow Rate for Asthma Monitoring}, booktitle = {Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS}, volume = {2020-July}, year = {2020}, note = {cited By 1}, pages = {5531-5536}, abstract = {The estimation of inhalation flow rate (IFR) using acoustic devices has recently received attention. While existing work often assumes that the microphone is placed at a fixed distance from the acoustic device, this assumption does not hold in real settings. This leads to poor estimation of the IFR since the received acoustic energy varies significantly with the distance. Despite the fact that the acoustic source is passive and only one microphone is used, we show in this paper that the distance can be estimated by exploiting the inhaler actuation sound, generated when releasing the medication. Indeed, this sound is used as a reference acoustic signal which is leveraged to estimate the distance in real settings. The resulting IFR estimation is shown to be highly accurate (R2 = 80.3\%). {\textcopyright} 2020 IEEE.}, keywords = {Acoustic devices, Acoustic energy, Acoustic signals, Acoustic sources, Highly accurate, Microphones}, doi = {10.1109/EMBC44109.2020.9175314}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091027116\&doi=10.1109\%2fEMBC44109.2020.9175314\&partnerID=40\&md5=33b9d02826be90a4bdc1aae587e1a8e3}, author = {Jeddi, Z. and Ghogho, M. and Bohr, A. and Boetker, J. and Li, Y. and Kassou, I.} } @conference {MacHhour2018206, title = {Concatenate text embeddings for text classification}, booktitle = {2017 International Conference on Internet of Things, Embedded Systems and Communications, IINTEC 2017 - Proceedings}, volume = {2018-January}, year = {2018}, pages = {206-210}, doi = {10.1109/IINTEC.2017.8325940}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050606189\&doi=10.1109\%2fIINTEC.2017.8325940\&partnerID=40\&md5=e76a80bf8a9cdf04c98aa3a746c22d4c}, author = {Machhour, H. and Kassou, I.} } @article {Oufkir201872, title = {Measuring knowledge management project performance}, journal = {Advances in Intelligent Systems and Computing}, volume = {745}, year = {2018}, pages = {72-81}, doi = {10.1007/978-3-319-77703-0_7}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045131625\&doi=10.1007\%2f978-3-319-77703-0_7\&partnerID=40\&md5=5e015ad9e8b84a851af4a4705e149472}, author = {Oufkir, L. and Kassou, I.} } @conference {Lahlou201864, title = {Textual context aware factorization machines: Improving recommendation by leveraging users{\textquoteright} reviews}, booktitle = {ACM International Conference Proceeding Series}, year = {2018}, pages = {64-69}, doi = {10.1145/3289100.3289111}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058629650\&doi=10.1145\%2f3289100.3289111\&partnerID=40\&md5=c2869c20ec04d08f675efb27e1536863}, author = {Lahlou, F.Z. and Benbrahim, H. and Kassou, I.} } @conference {Lahlou20163312, title = {Improving recommendations using context from users{\textquoteright} reviews}, booktitle = {Proceedings of the 27th International Business Information Management Association Conference - Innovation Management and Education Excellence Vision 2020: From Regional Development Sustainability to Global Economic Growth, IBIMA 2016}, year = {2016}, note = {cited By 0}, pages = {3312-3315}, abstract = {Recommender systems enable E-commerce websites to improve their sales by suggesting relevant items to customers. If considering the context of buying situations, more accurate recommendations can be computed. In this paper, we discuss the issue of using the contextual information contained in users{\textquoteright} reviews in order to improve recommendation. Copyright {\textcopyright} 2016 International Business Information Management Association}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984653667\&partnerID=40\&md5=a03c657d3c2b4702850bc5f2e897eb3a}, author = {Lahlou, F.Z. and Benbrahim, H. and Kassou, I.} } @conference {Amarouche20162876, title = {Introduction to competitive intelligence: Process, applications and tools}, booktitle = {Proceedings of the 27th International Business Information Management Association Conference - Innovation Management and Education Excellence Vision 2020: From Regional Development Sustainability to Global Economic Growth, IBIMA 2016}, year = {2016}, note = {cited By 0}, pages = {2876-2885}, abstract = {In the world of excessive business competitiveness, almost every company tries to monitor its environment to exceed the competitors. Getting knowledge about competitors is the basic principal of what is called Competitive Intelligence (CI). Many applications of Competitive Intelligence can be used like Opinion Mining and Foresight studies and the process of obtaining such intelligence differs according to the company{\textquoteright}s needs. In this paper, we will present in more details the definitions of CI and a general process grouping the most used steps in conducting such study. In the end we will present some tools useful in CI. Copyright {\textcopyright} 2016 International Business Information Management Association}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984646253\&partnerID=40\&md5=1c66c097dc1b53d274daa126d36a743f}, author = {Amarouche, K. and El Akrouchi, M. and Benbrahim, H. and Kassou, I.} } @article {Oufkir2016242, title = {Knowledge management performance measurement: A generic framework}, journal = {Communications in Computer and Information Science}, volume = {615}, year = {2016}, note = {cited By 0}, pages = {242-254}, abstract = {This theoretical article aims to propose a generic framework for measuring performance of Knowledge Management (KM) projects based on critical literature review. The proposed framework fills the existing gap on KM performance measurement in two points: (i) it provides a generic tool that is able to assess all kinds of KM project as well as the overall organization KM, (ii) it assesses KM projects according to KM objectives in a generic manner. Our framework (GKMPM) relies on a process reference model that provides a KM common understanding in a process based view. It is based on a goal-oriented measurement approach and considers that KM performance dimensions are stakeholder{\textquoteright}s objectives. The framework application follows a procedural approach that begins with the KM project modelling, followed by the objectives prioritization. The next step consists of collecting and analysing data for pre-designed measures, and produces a set of key performance indicators (KPIs) related to the KM project processes and in accordance with its objectives. {\textcopyright} Springer International Publishing Switzerland 2016.}, doi = {10.1007/978-3-319-40180-5_17}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979022041\&doi=10.1007\%2f978-3-319-40180-5_17\&partnerID=40\&md5=7353ebf3c020ba8a9bc9458832afda06}, author = {Oufkir, L. and Fredj, M. and Kassou, I.} } @conference {Oufkir20162744, title = {Towards a reference model for Knowledge Management performance measurement}, booktitle = {Proceedings of the 27th International Business Information Management Association Conference - Innovation Management and Education Excellence Vision 2020: From Regional Development Sustainability to Global Economic Growth, IBIMA 2016}, year = {2016}, note = {cited By 0}, pages = {2744-2755}, abstract = {Knowledge Management (KM) projects are socio-technical systems that enable knowledge activities and ensure that the right knowledge gets to the right person at the right time. The growing number of KM applications confirms the need for a performance measurement model able to assess the diversity of KM initiatives in order to rationalize their usage. To the best of our knowledge, a generic KM model for performance measurement fitting any kind of KM projects is missing in the literature. Instead, existing approaches are specific to a particular KM project or assess the overall KM of the organization. In this paper, we propose a KM model for performance measurement that is built on existing KM models literature and enhanced with theoretical findings. It also follows the reference modelling design process in view of producing a high quality model. Copyright {\textcopyright} 2016 International Business Information Management Association}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984611689\&partnerID=40\&md5=6ee42ddfe7a2a3ce0b1f2f99f09aa05b}, author = {Oufkir, L. and Fredj, M. and Kassou, I.} } @conference {Amarouche2015358, title = {Product Opinion Mining for Competitive Intelligence}, booktitle = {Procedia Computer Science}, volume = {73}, year = {2015}, note = {cited By 1}, pages = {358-365}, abstract = {Competitive Intelligence is one of the keys of companies Risk Management. It provides the company with a permanent lighting to its competitive environment. The increasingly frequent use of Information and Communication Technologies (ICT); including (namely) online shopping sites, blogs, social network sites, forums, provides incentives for companies check their advantages over their competitors. This information presents a new source that helps and leads the company to identify, analyze and manage the various risks associated with its business/products. Nowadays, a good use of these data helps the company to improve its products/services. In this paper, an overview of opinion mining for competitive intelligence will be presented. We{\textquoteright}ll try to synthesize the major research done for the different steps of product opinion mining. {\textcopyright} 2015 The Authors.}, doi = {10.1016/j.procs.2015.12.004}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962678879\&doi=10.1016\%2fj.procs.2015.12.004\&partnerID=40\&md5=6d1bc9b3ded99bfaf39408391296ee1d}, author = {Amarouche, K. and Benbrahim, H. and Kassou, I.} } @conference {ManarElBouanani2013, title = {An approach using intertextual distance to detect web messages authors}, booktitle = {2013 3rd International Symposium ISKO-Maghreb}, year = {2013}, note = {cited By 0}, abstract = {Our objective in this paper is to propose an approach capable of detecting authors of web messages based on specific vocabulary and Intertextual distance. Focus in the present work is on comparing the most popular distances using in the field of authorship detection namely Delta Rule, chi-square distance and Kullback-Leibler Divergence. {\textcopyright} 2013 IEEE.}, doi = {10.1109/ISKO-Maghreb.2013.6728130}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894116721\&doi=10.1109\%2fISKO-Maghreb.2013.6728130\&partnerID=40\&md5=8d06efee89428887463c60388b59a295}, author = {Manar El Bouanani, S.E. and Kassou, I.} } @conference {Lahlou2013, title = {Context extraction from reviews for Context Aware Recommendation using Text Classification techniques}, booktitle = {Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA}, year = {2013}, note = {cited By 0}, abstract = {In this paper, we investigate the use of Text Classification techniques to extract contextual information from user reviews for Context Aware Recommendation. We conduct several experiments to identify the best Text Representation settings and the best classification algorithm for our dataset. We carry out our experiments on hotel reviews. We focus on extracting the trip type, as contextual information, from these reviews. Results show that the Na{\"\i}ve Bayes classifier yields the best results with up to 72.2\% in terms of F1-measure. To extract context from user reviews with text classification techniques, we recommend to use raw text rather than employing stemming, to use the normalized frequency based weighting rather than the presence based one, to remove terms that occur once in the data set, and to combine unigrams, bigrams and trigrams. {\textcopyright} 2013 IEEE.}, doi = {10.1109/AICCSA.2013.6616512}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887248381\&doi=10.1109\%2fAICCSA.2013.6616512\&partnerID=40\&md5=efcaf96161103c978184c9ad286a22cd}, author = {Lahlou, F.Z. and Benbrahimand, H. and Mountassir, A. and Kassou, I.} } @conference {Machhour2013, title = {Dynamic text classifier based on search engine features}, booktitle = {2013 3rd International Symposium ISKO-Maghreb}, year = {2013}, note = {cited By 0}, abstract = {Search engines and text categorization are two research areas almost inseparable. Where one is studied, the other is referred sooner or later. Automatic text categorization became more important with the enormous increase of the online information, and text classifiers are often there to help search engines classify indexed documents. The main idea presented in this paper consists of using a search engine as a text classifier. A search engine can take advantage of its scoring performances to categorize a new document without requiring building and using other categorization model. K Nearest Neighbors (KNN) principal based on search engine score as similarity measure was used. This approach is highly dependent on the scoring quality of the used search engine. It is a simple approach but can be competitive to other more complex categorization models. Also, this method is useful as a kind of categorization on the fly when indexing a new document. Through its evolving index, the search engine becomes a dynamic classifier of the fact that any document, recently joining the index, participate in the categorization of other new documents. {\textcopyright} 2013 IEEE.}, doi = {10.1109/ISKO-Maghreb.2013.6728125}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894172340\&doi=10.1109\%2fISKO-Maghreb.2013.6728125\&partnerID=40\&md5=234e95731bc6177558b03187a1c03083}, author = {Machhour, H. and Kassou, I.} } @conference {Machhour201367, title = {Improving text categorization: A fully automated ontology based approach}, booktitle = {2013 3rd International Conference on Communications and Information Technology, ICCIT 2013}, year = {2013}, note = {cited By 1}, pages = {67-72}, abstract = {This paper presents an improvement of text categorization models by document annotation with previously imported ontologies. A fully automated algorithm will be introduced to annotate plain text documents. Simple strategies combining annotation results with the categorization models are also presented and experienced. Conducted experiments present an improvement of tested categorization models when mixed with the annotation results. {\textcopyright} 2013 IEEE.}, doi = {10.1109/ICCITechnology.2013.6579524}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883898536\&doi=10.1109\%2fICCITechnology.2013.6579524\&partnerID=40\&md5=2216baabb84bdd7324b7ec625a4eba68}, author = {Machhour, H. and Kassou, I.} } @conference {Lahlou2013, title = {A Text Classification based method for context extraction from online reviews}, booktitle = {2013 8th International Conference on Intelligent Systems: Theories and Applications, SITA 2013}, year = {2013}, note = {cited By 1}, abstract = {Recommender systems are systems that filter information depending on users{\textquoteright} profiles and suggest items that might match their preferences. While the majority of existing researches compute recommendation by considering only users and items, Context Aware Recommendation Systems (CARS) consider, in addition to users and items, others features related to the context. A first issue in CARS studies is to identify the contextual features. In this paper, we investigate the use of Text Classification techniques to extract contextual features from users{\textquoteright} reviews. We conduct experiments to identify the best classification algorithm for our dataset. We evaluate our approach on hotel reviews. We focus on extracting the trip type, as contextual information, from these reviews. Results show that the Multinomial Na{\"\i}ve Bayes performs best in our dataset, with a F1 score of 60.1\%. Since contextual information are not always provided in the reviews, we think that our results are promising. We conclude that this research area needs deeper studies. {\textcopyright} 2013 IEEE.}, doi = {10.1109/SITA.2013.6560804}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883074857\&doi=10.1109\%2fSITA.2013.6560804\&partnerID=40\&md5=440fb81da26cacbb428c326c7dc6cf50}, author = {Lahlou, F.Z. and Mountassir, A. and Benbrahim, H. and Kassou, I.} } @conference {ElBouanani20131494, title = {Using lexicometry and vocabulary analysis techniques to detect a signature for web profile}, booktitle = {Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013}, year = {2013}, note = {cited By 0}, pages = {1494-1498}, abstract = {Our research theme is evolving around the concept of computer profiling. The aim of our work is to propose an approach that will detect web profiles in a unique way and to model a print web for each profile. Our main concern is to find this signature from text messages in the forums, by analyzing the vocabulary used by each user. Also we will focus here on presenting our approach and our future work in a way that will allow us to detect the "Specific Vocabulary" for each web profile. Copyright 2013 ACM.}, doi = {10.1145/2492517.2558568}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893246694\&doi=10.1145\%2f2492517.2558568\&partnerID=40\&md5=d3d6a325ab8fd941a07351e2044dc572}, author = {El Bouanani, S.E.M. and Kassou, I.} } @conference {Machach2011325, title = {Mining social network data for decision support purposes in a teaching context}, booktitle = {Proceedings of the IADIS International Conference Information Systems 2011, IS 2011}, year = {2011}, note = {cited By 0}, pages = {325-329}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944034507\&partnerID=40\&md5=93b2a6856fcbb2ea953d1baa0ab4f50e}, author = {Machach, S. and Chiheb, R. and Kassou, I.} } @article {Elmeziane2008113, title = {A new artificial immune system for the detection of abnormal behaviour}, journal = {Studies in Computational Intelligence}, volume = {149}, year = {2008}, note = {cited By 1}, pages = {113-122}, doi = {10.1007/978-3-540-70560-4_10}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-52049089233\&doi=10.1007\%2f978-3-540-70560-4_10\&partnerID=40\&md5=d907d2de93d5249a4ec8aa418b36c4a9}, author = {Elmeziane, R. and Berrada, I. and Kassou, I.} }