Academic literature on the topic 'Recommandation de tag'
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Journal articles on the topic "Recommandation de tag"
Zullino, Hättenschwiler, Mattia, Stankovic, Khazaal, and Borgeat. "Pharmacothérapie de l'anxiété généralisée: Etat actuel." Praxis 92, no. 42 (October 1, 2003): 1775–79. http://dx.doi.org/10.1024/0369-8394.92.42.1775.
Full textFrost, Chris. "The Remuneration of Church Ministers in England: Examining Principles and Practice." European Journal of Theology 29, no. 1 (December 1, 2020): 62–74. http://dx.doi.org/10.5117/ejt2020.1.007.fras.
Full textFrost, Chris. "The Remuneration of Church Ministers in England: Examining Principles and Practice." European Journal of Theology 29, no. 1 (December 1, 2020): 62–74. http://dx.doi.org/10.5117/ejt2020.1.007.fras.
Full textNowotny, S. "Recommandations por la préparation et la distribution des aliments congelés —Recommendations for the processing and handling of frozen foods. 3. Aufl. 418 Seiten, zahlr. Abb. und Tab. Institut International du Froid, Paris 1986. Preis: 180,- FF." Food / Nahrung 31, no. 9 (1987): 929. http://dx.doi.org/10.1002/food.19870310929.
Full textDissertations / Theses on the topic "Recommandation de tag"
Gueye, Modou. "Gestion de données de recommandation à très large échelle." Electronic Thesis or Diss., Paris, ENST, 2014. http://www.theses.fr/2014ENST0083.
Full textIn this thesis, we address the scalability problem of recommender systems. We propose accu rate and scalable algorithms. We first consider the case of matrix factorization techniques in a dynamic context, where new ratings..are continuously produced. ln such case, it is not possible to have an up to date model, due to the incompressible time needed to compute it. This happens even if a distributed technique is used for matrix factorization. At least, the ratings produced during the model computation will be missing. Our solution reduces the loss of the quality of the recommendations over time, by introducing some stable biases which track users' behavior deviation. These biases are continuously updated with the new ratings, in order to maintain the quality of recommendations at a high leve for a longer time. We also consider the context of online social networks and tag recommendation. We propose an algorithm that takes account of the popularity of the tags and the opinions of the users' neighborhood. But, unlike common nearest neighbors' approaches, our algorithm doe not rely on a fixed number of neighbors when computing a recommendation. We use a heuristic that bounds the network traversai in a way that allows to faster compute the recommendations while preserving the quality of the recommendations. Finally, we propose a novel approach that improves the accuracy of the recommendations for top-k algorithms. Instead of a fixed list size, we adjust the number of items to recommend in a way that optimizes the likelihood that ail the recommended items will be chosen by the user, and find the best candidate sub-list to recommend to the user
Hmimida, Manel. "Une nouvelle approche topologique pour la recommandation de tags dans les folksonomies." Thesis, Paris, CNAM, 2015. http://www.theses.fr/2015CNAM1054/document.
Full textWe focus in this thesis on the problem of tag recommendation in social sharing to classification systems called folksonomies. Users of a folksonomy annotate their resources with freely tags chosen. We propose here a new topological approach for tags recommendation called TLTR (Two Level Tag Recommendation). TLTR (Two Level Tag Recommendation) is based on an original approach of graph compression. The graph of a folksonomy is compressed by a clustering each of the three components, namely the set of users, resources and tags. A topological clustering method based on a seed-centered approach for community detection in multiplex graphs is proposed. A classical topological approach, namely Folkrank, is applied to the reduced graph to select the most appropriate clusters of tags. These clusters are then used to build another contextual graph extracted from the original graph representing the folksonomy. Folkrank method is applied again to compute the list of tags to recommend. Experiments on large folksonomy, including, data extracted from references system Bibsonomy show the relevance of our approach
Mezghani, Manel. "Analyse des réseaux sociaux : vers une adaptation de la navigation sociale." Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30127/document.
Full textThe advent of Web 2.0, user-centered, has given rise to a significant amount of information (personal, collective, shared, "loved", etc.). This information is a way to help users and guide them to the information sought. However, this quantity makes access to shared information more and more difficult, given the diversity of content that may interest the user. Disorientation of the user is one of the main problems related to social media. To overcome such problem, adaptation is a standard solution that can be applied in a social context. With the evolution of these social networks, new concepts appear such as social navigation, which is a way to navigate while being influenced by other users in the network: Another important concept is that of "tag". This term is defined as social annotations created by users and associated to resources. Navigation can be therefore carried out by both links and tags. Adapting social navigation means making it more targeted for each user according to their interests. In practice, this can be done by recommending tags to each user, so he can follow or not. To adapt the social navigation, we must ensure proper detection of the user's interests and taking into account their evolution. However, we are faced with some problems: i) the detection of interest, since they can be derived from several social resources (friends, resources, tags, etc.). Their relevance is primordial to ensure adequate adaptation result. ii) updating the user profile. Indeed, the social user, is characterized by its great social activity, and therefore its interests should reflect its "real" interest each time period in order to achieve a reliable adaptation. To solve the problems affecting the quality of adaptation of social navigation quoted above, we first proposed a method for detecting the user's interests. This proposal aims to overcome the detection of irrelevant interests issues. This approach analyzes the user tags depending on the content of their respective resources. Unlike most research, who do not consider the accuracy of tags with the contents of resource, the accuracy reflects whether the user is really interested with the content or not. This is done by querying the user's network and analysis of the user annotation behavior. The approach is based on the assumption that a user annotates the resource by tags reflecting the content of this resource better reflects its "true" interests. Following the proposal of the interests of detection approach, we conducted second, the treatment of the problem of updating these interests. We were interested to the user profile enrichment techniques, performed by adding interests deemed relevant at a given time. The enrichment in a social context is performed according to social information such as neighbours who share the user behaviors in common, according to the user annotation behavior, and according to the metadata annotated resources. The choice of such information shall follow the study of their influence on the changing interests of the user. The approach we used enrichment propose recommendations (tags) according to the new tags added to the user profile. Both contributions were tested on the social database Delicious. They showed a sizeable accuracy rate. They have also proven their efficiency compared to conventional methods. In addition, the rate of ambiguity associated with the tags has been greatly reduced, thanks to the implicit filtering of irrelevant tags relative to resource content
Books on the topic "Recommandation de tag"
Programme national de lutte contre le SIDA/MST (Gabon), ed. Traitement par les antirétroviraux (TAR) des personnes vivant avec le VIH au Gabon: Recommandations du groupe d'experts. [Libreville]: République gabonaise, Ministère de la santé publique, Programme national de lutte contre le SIDA, 2005.
Find full textBook chapters on the topic "Recommandation de tag"
"Appendice. Recommandation du Conseil sur la détermination des prix de transfert entre entreprises associées [C(95)126/FINAL]." In Principes de l'OCDE applicables en matière de prix de transfert à l'intention des entreprises multinationales et des administrations fiscales 2010, 403–5. OECD, 2010. http://dx.doi.org/10.1787/tpg-2010-20-fr.
Full textConference papers on the topic "Recommandation de tag"
de Cidrac, L., L. Radoï, R. Pecorari, and T. Nguyen. "Tumeur à cellules géantes : à propos d’un cas récidivant et agressif à localisation mandibulaire." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206603021.
Full textReports on the topic "Recommandation de tag"
Taherizadeh, Amir, and Cathrine Beaudry. Vers une meilleure compréhension de la transformation numérique optimisée par l’IA et de ses implications pour les PME manufacturières au Canada - Une recherche qualitative exploratoire. CIRANO, June 2021. http://dx.doi.org/10.54932/jdxb2231.
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