International Conference Papers
Permanent URI for this collectionhttp://dl.cerist.dz/handle/CERIST/4
Browse
207 results
Search Results
Item Combining Tags and Reviews to Improve Social Book Search Performance(Springer, 2018-08-15) Chaa, Messaoud; Nouali, Omar; Bellot, PatriceThe emergence of Web 2.0 and social networks have provided important amounts of information that led researchers from different fields to exploit it. Social information retrieval is one of the areas that aim to use this social information to improve the information retrieval performance. This information can be textual, like tags or reviews, or non textual like ratings, number of likes, number of shares, etc. In this paper, we focus on the integration of social textual information in the research model. As it seems logical that integrating tags in the retrieval model should not be in the same way taken to integrate reviews, we will analyze the different influences of using tags and reviews on both the settings of retrieval parameters and the retrieval effectiveness. After several experiments, on the CLEF social book search collection, we concluded that combining the results obtained from two separate indexes and two models with specific parameters for tags and reviews gives good results compared to when using a single index and a single model.Item Face and kinship image based on combination descriptors-DIEDA for large scale features(IEEE, 2018-12-30) Aliradi, Rachid; Belkhir, Abdelkader; Ouamane, Abdelmalik; Aliane, HassinaIn this paper, we introduce an efficient linear similarity learning system for face verification. Humans can easily recognize each other by their faces and since the features of the face are unobtrusive to the condition of illumination and varying expression, the face remains as an access of active recognition technique to the human. The verification refers to the task of teaching a machine to recognize a pair of match and non-match faces (kin or No-kin) based on features extracted from facial images and to determine the degree of this similarity. There are real problems when the discriminative features are used in traditional kernel verification systems, such as concentration on the local information zones, containing enough noise in non-facing and redundant information in zones overlapping in certain blocks, manual adjustment of parameters and dimensions high vectors. To solve the above problems, a new method of robust face verification with combining with a large scales local features based on Discriminative-Information based on Exponential Discriminant Analysis (DIEDA). The projected histograms for each zone are scored using the discriminative metric learning. Finally, the different region scores corresponding to different descriptors at various scales are fused using Support Vector Machine (SVM) classifier. Compared with other relevant state-of-the-art work, this system improves the efficiency of learning while controlling the effectiveness. The experimental results proved that both of these two initializations are efficient and outperform performance of the other state-of-the-art techniques.Item IoT-DMCP: An IoT data management and control platform for smart cities(SCITEPRESS – Science and Technology Publications, 2019) Boulkaboul, Sahar; Djenouri, Djamel; Bouhafs, Sadmi; Belaid, MohandThis paper presents a design and implementation of a data management platform to monitor and control smart objects in the Internet of Things (IoT). This is through IPv4/IPv6, and by combining IoT specific features and protocols such as CoAP, HTTP and WebSocket. The platform allows anomaly detection in IoT devices and real-time error reporting mechanisms. Moreover, the platform is designed as a standalone application, which targets at extending cloud connectivity to the edge of the network with fog computing. It extensively uses the features and entities provided by the Capillary Networks with a micro-services based architecture linked via a large set of REST APIs, which allows developing applications independently of the heterogeneous devices. The platform addresses the challenges in terms of connectivity, reliability, security and mobility of the Internet of Things through IPv6. The implementation of the platform is evaluated in a smart home scenario and tested via numeric results. The results show low latency, at the order of few ten of milliseconds, for building control over the implemented mobile application, which confirm realtime feature of the proposed solution.Item Object Detection in Images Based on Homogeneous Region Segmentation(Springer, 2018) Amrane, Abdesalam; Meziane, Abdelkrim; Boulkrinat, Nour El HoudaImage segmentation for object detection is one of the most fundamental problems in computer vision, especially in object-region extraction task. Most popular approaches in the segmentation/object detection tasks use sliding-window or super-pixel labeling methods. The first method suffers from the number of window proposals, whereas the second suffers from the over-segmentation problem. To overcome these limitations, we present two strategies: the first one is a fast algorithm based on the region growing method for segmenting images into homogeneous regions. In the second one, we present a new technique for similar region merging, based on a three similarity measures, and computed using the region adjacency matrix. All of these methods are evaluated and compared to other state-of-the-art approaches that were applied on the Berkeley image database. The experimentations yielded promising results and would be used for future directions in our work.Item A genetic algorithm feature selection based approach for Arabic Sentiment Classification(IEEE Computer Society, 2016-11-29) Aliane, Hassina; Aliane, A.A; Ziane, M.; Bensaou, N.With the recently increasing interest for opinion mining from different research communities, there is an evolving body of work on Arabic Sentiment Analysis. There are few available polarity annotated datasets for this language, so most existing works use these datasets to test the best known supervised algorithms for their objectives. Naïve Bayes and SVM are the best reported algorithms in the Arabic sentiment analysis literature. The work described in this paper shows that using a genetic algorithm to select features and enhancing the quality of the training dataset improve significantly the accuracy of the learning algorithm. We use the LABR dataset of book reviews and compare our results with LABR’s authors’ results.Item Automatic Construction of Ontology from Arabic Texts(Université Djillali LIABES Sidi-Bel-Abbès, 2012-04-29) Mazari, Ahmed Cherif; Aliane, Hassina; Alimazighi, ZaiaThe work which will be presented in this paper is related to the building of an ontology of domain for the Arabic linguistics. We propose an approach of automatic construction that is using statistical techniques to extract elements of ontology from Arabic texts. Among these techniques we use two; the first is the "repeated segment" to identify the relevant terms that denote the concepts associated with the domain and the second is the "co-occurrence" to link these new concepts extracted to the ontology by hierarchical or non- hierarchical relations. The processing is done on a corpus of Arabic texts formed and prepared in advance.Item A Graph Approach for Enhancing Process Models Matchmaking(IEEE, 2015-06-27) Belhoul, Yacine; Yahiaoui, Saïd; Haddad, Mohammed; Gater, Ahmed; Kheddouci, Hamamache; Bouzeghoub, MokraneRecent attempts have been done to measure similarity of process models based on graph matching. This problem is known to be difficult and its computational complexity is exponential. Thus, heuristics should be proposed to obtain approximations. Spectral graph matching methods, in particular eigenvalue-based projections, are know to be fast but they lost some quality in the obtained matchmaking. In this paper, we propose a graph approach for the problem of inexact matching of process models. Our approach combines a spectral graph matching method and a string comparator based algorithm in order to improve the quality of process models matchmaking. The proposed method performs the matchmaking at both structural and semantic levels. Experimentation is provided to show the performance of our method to rank a collection of process models according to a particular user query, compared to previous work.Item آليات ردع السرقات العلمية في البحوث الاجتماعية: البوابة الوطنية للإشعار عن الأطروحات نموذجا(مخبر الدراسات القانونية و مسؤولية المهنيين بجامعة طاهري محمد بشار, 2019-12-15) مبتوش, نوالRésumé : لقد تفشت ظاهرة السرقة العلمية في الجامعات الجزائرية و أصبحت محل اهتمام العديد من الأكاديميين و الباحثين من مختلف التخصصات. حيث أنها تفاقمت بشكلٍ ملحوظٍ في السنوات الأخيرة عند طلبة السنوات النهائية لمختلف الأطوار الجامعية، لاسيما في ما يخص مذكرات ما بعد التدرج الماجستير,الدكتوراه,الدكتوراه ل.م.د فالسرقة العلمية جريمة أخلاقية, حيث يقوم الباحث أو الطالب بالاستغلال مجهودات غيره و ينتسبها لنفسه بدون أي وجه حق. وهذا يتنافى مع مبدأ الأمانة العلمية والنزاهة الأكاديمية. وفي هذا الصدد تعتبر البوابة الوطنية للإشعار عن الأطروحات الوسيلة الشاملة للوصول إلى الإنتاج العلمي للباحثين فيما يخص الأطروحات (ماجستير، دكتوراه، دكتوراه LMD) على المستوى الوطني, و التي يمكن من خلالها تجنب تكرار مواضيع الأطروحات و انتحالها.تم تطوير البوابة الوطنية لإشعار عن الأطروحات في عام 2010 من طرف مركز البحث في الإعلام العلمي و التقني ,بطلب من وزارة التعليم العالي و البحث العلمي.Item Fully-Functional Bidirectional Burrows-Wheeler Indexes and Infinite-Order De Bruijn Graphs(Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2019-06-18) Belazzougui, Djamal; Cunial, FabioGiven a string T on an alphabet of size σ, we describe a bidirectional Burrows-Wheeler index that takes O(|T| log σ) bits of space, and that supports the addition and removal of one character, on the left or right side of any substring of T, in constant time. Previously known data structures that used the same space allowed constant-time addition to any substring of T, but they could support removal only from specific substrings of T. We also describe an index that supports bidirectional addition and removal in O(log log |T|) time, and that takes a number of words proportional to the number of left and right extensions of the maximal repeats of T. We use such fully-functional indexes to implement bidirectional, frequency-aware, variable-order de Bruijn graphs with no upper bound on their order, and supporting natural criteria for increasing and decreasing the order during traversal.Item Computing the Antiperiod(s) of a String(Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2019-06-18) Alamro, Hayam; Badkobeh, Golnaz; Belazzougui, Djamal; Iliopoulos, Costas S.; Puglisi, Simon J.A string S[1, n] is a power (or repetition or tandem repeat) of order k and period n/k, if it can be decomposed into k consecutive identical blocks of length n/k. Powers and periods are fundamental structures in the study of strings and algorithms to compute them efficiently have been widely studied. Recently, Fici et al. (Proc. ICALP 2016) introduced an antipower of order k to be a string composed of k distinct blocks of the same length, n/k, called the antiperiod. An arbitrary string will have antiperiod t if it is prefix of an antipower with antiperiod t. In this paper, we describe efficient algorithm for computing the smallest antiperiod of a string S of length n in O(n) time. We also describe an algorithm to compute all the antiperiods of S that runs in O(n log n) time.