104 research outputs found
Document numérique dynamique : une étoile filante dans l\u27espace documentaire (Le)
Intervention au colloque "Le numérique : impact sur le cycle de vie du document", organisé à l\u27université de Montréal par l\u27EBSI et l\u27ENSSIB du 13 au 15 octobre 2004. La majorité de pages Web existantes actuellement sont des pages Web créées dynamiquement. Ces documents qui n\u27existent pas réellement, sont créés pour une demande individuelle (automatique ou manuelle) et ils disparaissent après leur consultation. Cet article s\u27intéresse aux problèmes de la durée d\u27existence, d\u27accessibilité et d\u27archivage de ces pages. Les différentes définitions, catégorisation des documents dynamiques et leur mise en oeuvre sont introduites dans un premier temps pour ensuite analyser les résultats de différents tests statistiques effectués dans l\u27objectif d\u27évaluation de durée de vie de documents numériques dynamiques
Graph based System Purpose - Built for Automatic Retrieval and Extraction of the Electronics Data
International audienceThe work presented in this paper concerns automatic information retrieval and extraction in precise field of electronics based on linguistic knowledge. The extraction and the filtering of data is carried out automatical ly by methods based on the construction of local grammar. To carry out an automatic search for the events in the corpus, a linguistic base, for example the base of the graphs, was created. A comparison of methods is given
RRSS - Rating Reviews Support System Purpose Built for Movies Recommendation.
International audienceThis paper describes the part of a recommendation system designed for the recognition of film reviews (RRSS). Such a system allows the automatic collection, evaluation and rating of reviews and opinions of the movies. First the system searches and retrieves texts supposed to be movie reviews from the Internet. Subsequently the system carries out an evaluation and rating of the movie reviews. Finally, the system automatically associates a digital assessment with each review. The goal of the system is to give the score of reviews associated with the user who wrote them. All of this data is the input to the cognitive engine. Data from our base allows the making of correspondences, which are required for cognitive algorithms to improve, advanced recommending functionalities for e-business and e-purchase websites. In this paper we will describe the different methods on auto- matically identifying opinions using natural language knowledge and techniques of classification
An autonomous system designed for automatic detection and rating of film reviews. Extraction and linguistic analysis of sentiments.
International audienceThis paper describes the functions of a system designed for the assessment of movie reviews. Such a system enables the automatic collection, evaluation and rating of film critics' opinions of movies. First the system searches and retrieves probable movie reviews from the Internet, especially those expressed by prolific reviewers. Subsequently the system carries out an evaluation and rating of those movie reviews. Finally the system automatically associates a numerical mark to each review, this is the objective of the system. This data constitutes the input to the cognitive engine. Our system uses three different methods for classifying opinions in critics' reviews. We introduce two new methods based on linguistic knowledge. Results are then compared with the overall statistical method using Bays classifier. The last step is to combine the results obtained in order to make the final assessment as accurately as possible
Tool of the Intelligence Economic: Recognition Function of Reviews Critics. Extraction and linguistic Analysis of sentiments.
International audienceThis paper describes the part of recommender system designed for movies' critics recognition. Such a system allows the automatic collection, evaluation and rating of critics and opinions of the movies. First the system searches and retrieves texts supposed to be movies' reviews from the Internet. Subsequently the system carries out an evaluation and rating of movies' critics. Finally the system automatically associates a numerical mark to each critic. The goal of system is to give the score of critics associated to the users' who wrote them. All of this data are the input to the cognitive engine. Data from our base allow making correspondences which are required for cognitive algorithms to improve advanced recommending functionalities for e-business and e-purchases websites. Our sesystem uses three different methods for classifying opinions from reviews critics. In this paper we describe the part of system which is based on automatically identifying opinions using natural language processing knowledge
Social Network - An autonomous system designed for radio recommendation.
International audienceThis paper describes the functions of a system proposed for the music tube recommendation from social network data base. Such a system enables the automatic collection, evaluation and rating of music critics, the possibility to rate music tube by auditors and the recommendation of tubes depended from auditor's pro les in form of regional internet radio. First, the system searches and retrieves probable music reviews from the Internet. Subsequently, the system carries out an evaluation and rating of those reviews. From this list of music tubes the system directly allows notation from our application. Finally the system automatically create the record list di used each day depended form the region, the year season, day hours and age of listeners. Our system uses linguistics and statistic methods for classifying music opinions and data mining techniques for recommendation part needed for recorded list creation. The principal task is the creation of popular intelligent radio adaptive on auditor's age and region - IA-Regional-Radio
IA-Regional-Radio - social network for radio recommendation
International audienceThis chapter describes the functions of a system proposed for the music hit recommendation from social network data base. This system carries out the automatic collection, evaluation and rating of music reviewers, the possibility for listeners to rate musical hits and recommendations deduced from auditor's pro les in the form of regional internet radio. First, the system searches and retrieves probable music reviews from the Internet. Subsequently, the system carries out an evaluation and rating of those reviews. From this list of music hits the system directly allows notation from our application. Finally the system automatically create the record list di used each day depended form the region, the year season, day hours and age of listeners. Our system uses linguistics and statistic methods for classifying music opinions and data mining techniques for recommendation part needed for recorded list creation. The principal task is the creation of popular intelligent radio adaptive on auditor's age and region - IA-Regional-Radio
Textual entailment by generality
Available online 7 December 2011International audienceTextual Entailment consists in determining if an entailment relation exists between two texts. In this paper, we present an Informative Asymmetric Measure called the Asymmetric InfoSimba (AIS), which we combine with different asym-metric association measures to recognize the specific case of Textual Entailment by Generality. In particular, the AIS proposes an unsupervised, language-independent, threshold free solution. This new measure is tested against the first Recognizing Textual Entailment dataset for an exhaustive number of asymmetric association measures and shows that the combination of the AIS with the Braun-Blanket steadily improves results against competitive measures such as the one proposed by [1]
Time-Dependent Influence Measurement in Citation Networks
In every scientific discipline, researchers face two common dilemmas: where to find bleeding-edge papers and where to publish their own articles. We propose to answer these questions by looking at the influence between communities, e.g. conferences or journals. The influential conferences are those which papers are heavily cited by other conferences, i.e. they are visible, significant and inspiring. For the task of finding such influential places-to-publish, we introduce a Running Influence model that aims to discover pairwise influence between communities and evaluate the overall influence of each considered community. We have taken into consideration time aspects such as intensity of papers citations over time and difference of conferences starting years. The community influence analysis is tested on real-world data of Computer Science conferences
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