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5th Symposium on Languages, Applications and Technologies, SLATE 2016

作者： Mbarek, Rabeb Tmar, Mohamed Hattab, Hawete Boughanem, Mohand Sfax University Multimedia Information Systems and Advanced Computing Laboratory Sfax Tunisia Umm Al-Qura University Department of Mathematics Makkah Saudi Arabia University of Toulouse IRIT Lab France Toulouse France

ISBN: (纸本)9783959770064

In this paper, we propose a novel approach for document re-ranking, which relies on the concept of negative feedback represented by irrelevant documents. In a previous paper, a pseudo-relevance feedback method is introduced using an absorbing document d which best fits the user's need. The document d is orthogonal to the majority of irrelevant documents. In this paper, this document is used to re-rank the initial set of ranked documents in Ad-hoc retrieval. The evaluation carried out on a standard document collection shows the effectiveness of the proposed approach. © Rabeb Mbarek, Mohamed Tmar, Hawete Hattab, and Mohand Boughanem;licensed under Creative Commons License CC-BY.

关键词： Absorption of irrelevance Re-ranking Vector product

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Arabic named entity recognition process using transducer cascade and Arabic wikipedia 10

Arabic named entity recognition process using transducer cas...

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10th International Conference on Recent Advances in Natural Language Processing, RANLP 2015

作者： Mesmia, Fatma Ben Friburger, Nathalie Haddar, Kais Maurel, Denis University of Sfax Laboratory MIRACL Multimedia InfoRmation Systems and Advanced Computing Laboratory Tunisia University François Rabelais of Tours LI Computer laboratory France

Transducers namely transducer cascades are used in several NLP-applications such as Arabic named entity recognition (ANER). To experiment and evaluate an ANER process, a weight coverage corpus is necessary. In this paper, we propose an ANER method based on transducer cascade. The proposed transducer cascade is generated with the CasSys tool integrated in Unitex linguistic platform. The experimentation of our method is done on a Wikipedia corpus. The Wikipedia text format is obtained with Kiwix tool. The experiment results are satisfactory based on calculated measures.

关键词： Transducers

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Transducers cascades for an automatic recognition of Arabic named entities in order to establish links to free resources 1

Transducers cascades for an automatic recognition of Arabic ...

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1st International Conference on Arabic Computational Linguistics, ACLing 2015

作者： Mesmia, Fatma Ben Friburger, Nathalie Haddar, Kais Maurel, Denis University of Sfax Laboratory MIRACL Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax Tunisia University of François Rabelais of Tours LI Computer Laboratory Tours France

ISBN: (纸本)9781467391559

Arabic named entities (ANE) are often sources of information. That is why they are used by several applications of natural language processing (NLP) mainly in information retrieval. In order to improve the relevance of the information obtained, links to free resources can be established. Indeed, the recognition of these entities requires the use of adequate formalisms. In this paper, we propose an approach based on transducer cascades which allows the recognition of ANE more precisely the dates. This categorycan be an integral part in the events and the names of places. The implementation of the developed transducers cascades elaborated by using the CasSys tool is available under the Unitex platform. The results are motivating. © 2015 IEEE.

关键词： Transducers

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An UML class recommender system for software design

An UML class recommender system for software design

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ACS/IEEE International Conference on Computer systems and Applications

作者： Akil Elkamel Mariem Gzara Hanene Ben-Abdallah Faculty of Computing and Information Technology Northern Border University Rafha KSA Multimedia InfoRmation systems and Advanced Computing Laboratory University of Sfax Tunisia Higher School of Computer Science and Mathematics University of Monastir Tunisia Faculty of Computing and Information Technology King Abdulaziz University Jeddah KSA

Recommendation systems provide suggestions for items that are potentially interesting for a user in a given context. The provided recommendations are extracted generally from a huge amount of data collected from several sources of information. Thus a recommendation system requires firstly a pre-treatment step to prepare the data and secondly the application of some techniques such as data mining techniques to handle and extract the knowledge to be recommended to the user from the data. Our contribution consists on proposing a Recommendation System for Software Engineering (RSSE). This system recommends UML classes in the design phase of UML classes diagrams. Our RSSE is composed by two main phases: an off-line phase in which we use a clustering algorithm to partition UML classes collected from several UML classes diagrams based on the semantic relations existing between their characteristics. We have defined a metric that measures the similarity between UML classes. The second is an online phase in which we use the obtained clusters of UML classes to propose suggestions to the user based on elements added to his UML classes diagram under construction. The proposed system is then experimentally evaluated by using a UML classes corpus collected from several UML classes diagrams. The experimental evaluation shows very encouraging ratio of useful recommendations.

关键词： Unified modeling language Software Software engineering Recommender systems Computer architecture Databases Collaboration

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ETL transformation algorithm for Facebook opinion data 11

ETL transformation algorithm for Facebook opinion data

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11th International Conference on Web information systems and Technologies, WEBIST 2015

作者： Walha, Afef Ghozzi, Faiza Gargouri, Faïez Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax Tunisia Institute of Computer Science and Multimedia Sfax University Sfax Tunisia

ISBN: (纸本)9789897581069

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.

关键词： Sentiment analysis

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Indexing and classifiying Video Genres using Support Vector Machines

Indexing and classifiying Video Genres using Support Vector ...

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IEEE/ACS International Conference on Computer systems and Applications

作者： Nouha Dammak Yassine BenAyed Multimedia InfoRmation system and Advanced Computing Laboratory MIRACL Sfax Tunisia

ISBN: (纸本)9781509004799

In this paper, classifying and indexing hierarchical video genres using Support Vector Machines (SVMs) are based on only audio features. In fact, segmentation parameters are extracted at block levels, which have a major benefit by capturing local temporal information. The main contribution of our study is to present a powerful combination between the two employed audio descriptors;Mel Frequency Cepstral Coefficients (MFCC) and signal energy in order to classify a big YouTube dataset that includes multi-Arabic dialects video genres and even sub-genres: several sports analysis and various matches categories (foot-ball, basket-ball, hand-ball and volley-ball), both studio and fields news scenes over and above various multi-singer and multi-instruments music clips. Validation of this approach was carried out on over 18 hours of video span yielding a classification accuracy of 98,5% for genres, 97% for sports subgenres and 76% for music sub-genres. Finally we discuss SVM kernels performance on our proposed dataset.

关键词： audio feature classification hierarchical segmentation support vector machine video genre

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Decision tree transformation for knowledge warehousing 17

Decision tree transformation for knowledge warehousing

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17th International Conference on Enterprise information systems, ICEIS 2015

作者： Ayadi, Rim Hachaichi, Yasser Alshomrani, Saleh Feki, Jamel Multimedia InfoRmation Systems and Advanced Computing Laboratory Sakiet Ezzit Tunisia University of Sfax Sfax Tunisia Faculty of Computing and IT University of Jeddah Jeddah Saudi Arabia

ISBN: (纸本)9789897580970

Explicit knowledge extracted from data, formalized tacit knowledge from experts or even knowledge existing in business sources may be in several heterogeneous formal representations and structures: as rules, models, functions, etc. However, a knowledge warehouse should solve this structural heterogeneity before storing knowledge. This requires specific tasks of harmonizing. This paper first presents our proposed definition and architecture of a knowledge warehouse, and then presents some languages for knowledge representations as particular the MOT (Modeling with Object Types) language. In addition, we suggest a metamodel for the MOT, and a metamodel for the explicit knowledge obtained using decision trees technique. As we aim to represent knowledge having different modeling formalisms into MOT, as a unified model, then we suggest a set of transformation rules that assure the move from the decision tree source model into the MOT target model. This work is still in progress, it is currently completed with tranformations for additional.

关键词： Data mining

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Graphical Models for Multi-dialect Arabic Isolated Words Recognition

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Procedia Computer Science 2015年 60卷 508-516页

作者： Elyes Zarrouk Yassine BenAyed Faiez Gargouri MIRACL Multimedia InfoRmation system and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia ISIMS University of Sfax Tunisia.

This paper presents the use of multiple hybrid systems for the recognition of isolated words from a large multi-dialect Arabic vocabulary. Such as the Hidden Markov models (HMM), Dynamic Bayesian networks (DBN) lack a discriminatory ability especially on speech recognition even if their progress is huge. Multi-Layer perceptrons (MLP) was applied in literature as an estimator of emission probabilities in HMM and proves it effectiveness. In order to ameliorate the results of recognition systems, we apply Support Vectors Machine (SVM) as an estimator of posterior probabilities since they are characterized by a high predictive power and discrimination. Moreover, they are based on a structural risk minimization (SRM) where the aim is to set up a classifier that minimizes a bound on the expected risk, rather than the empirical risk. In this work we have done a comparative study between three hybrid systems MLP/HMM, SVM/HMM and SVM/DBN and the standards models of HMM and DBN. In this paper, we describe the use of the hybrid model SVM/DBN for multi-dialect Arabic isolated words recognition. So, by using 67,132 speech files of Arabic isolated words, this work arises a comparative study of our acknowledgment system of it as the following: the use of especially the HMM standards leads to a recognition rate of 74.18%.as the average rate of 8 domains for everyone of the 4 dialects. Also, with the hybrid systems MLP/HMM and SVM/HMM we succeed in achieving the value of 77.74%.and 7806% respectively. Moreover, our proposed system SVM/DBN realizes the best performances, whereby, we achieve 87.67% as a recognition rate more than 83.01% obtained by GMM/DBN.

关键词： graphical models hidden markov models dynamic bayesian networks supports vecotrs machine multi-layer perceptrons isoalted words recognition.

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A formal modeling method to enrich the Arabic treebank ATB with syntactic properties 7

A formal modeling method to enrich the Arabic treebank ATB w...

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7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015

作者： Bahloul, Raja Bensalem Haddar, Kais Blache, Philippe Multimedia InfoRmation Systems and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia Sfax Tunisia Laboratoire Parole et Langage CNRS Université de Provence Aix-en-Provence France

ISBN: (纸本)9789897581588

The enrichment of an Arabic treebank with syntactic properties can facilitate many types of parsing processes. This enrichment allows also the increase of its use in different NLP applications, the acquirement of new linguistic resources and the ease of the probabilistic parsing process by using statistics to limit the properties to the satisfied ones or to the most frequent ones. In this context, our proposed enrichment method is based on a formalization phase, a Property Grammar induction phase from a source treebank and a treebank regeneration phase with a new syntactic property-based representation. Starting with a formalization phase in our enrichment problem may succeed its resolution procedure. In fact, it limits the specification of the data sets and the interactions between them to the used ones, which avoids any duplication. The formalization allows also the anticipation of the constraints to respect in the problem. The implementation of this enrichment method is experimented essentially on the Arabic treebank ATB. This experiment provides us with good and encouraging results and various properties of different types. Copyright © 2015 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Modeling languages

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3D Ear Shape Matching Using Joint -Entropy

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Journal of Computer Science & Technology 2015年第3期30卷 565-577页

作者：孙晓鹏李思慧韩枫魏小鹏 Institute of Computer Systems School of Computer and Information Technology Liaoning Normal University Dalian 116029 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China School of Mechanical and Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian 116622 China

In this article, we investigate the use of joint a-entropy for 3D ear matching by incorporating the local shape feature of 3D ears into the joint a-entropy. First, we extract a sut^cient number of key points from the 3D ear point cloud, and fit the neighborhood of each key point to a single-value quadric surface on product parameter regions. Second, we define the local shape feature vector of each key point as the sampling depth set on the parametric node of the quadric surface. Third, for every pair of gallery ear and probe ear, we construct the minimum spanning tree （MST） on their matched key points. Finally, we minimize the total edge weight of MST to estimate its joint a-entropy the smaller the entropy is, the more similar the ear pair is. We present several examples to demonstrate the advantages of our algorithm, including low time complexity, high recognition rate, and high robustness. To the best of our knowledge, it is the first time that, in computer graphics, the classical information theory of joint a-entropy is used to deal with 3D ear shape recognition.

关键词： joint a-entropy minimum spanning tree local shape feature ear matching ear recognition

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