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Dissertations / Theses on the topic 'Large Scale Recommendation'

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1

Nilsen, John Eirik Bjørhovde. "Large-Scale User Click Analysis in News Recommendation." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23004.

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The Internet and the World Wide Web have taken over as the standard reading and finding news. This makes it possible for news readers to carefully choose the news that is most interesting for them. Due to the large amounts of articles, it can be a challenging and time consuming task to find the wanted information. Simplifying this process for the news readers would be beneficial.This thesis explores the idea of filtering out unwanted news articles and serving the useful ones to the reader through mobile platforms. It is part of a bigger project named SmartMedia that focuses on using complex st
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Larsson, Carl-Johan. "Movie Recommendation System Using Large Scale Graph-Processing." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-200601.

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3

Sakhi, Otmane. "Offline Contextual Bandit : Theory and Large Scale Applications." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAG011.

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Cette thèse s'intéresse au problème de l'apprentissage à partir d'interactions en utilisant le cadre du bandit contextuel hors ligne. En particulier, nous nous intéressons à deux sujets connexes : (1) l'apprentissage de politiques hors ligne avec des certificats de performance, et (2) l'apprentissage rapide et efficace de politiques, pour le problème de recommandation à grande échelle. Pour (1), nous tirons d'abord parti des résultats du cadre d'optimisation distributionnellement robuste pour construire des bornes asymptotiques, sensibles à la variance, qui permettent l'évaluation des performa
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4

Safran, Mejdl Sultan. "EFFICIENT LEARNING-BASED RECOMMENDATION ALGORITHMS FOR TOP-N TASKS AND TOP-N WORKERS IN LARGE-SCALE CROWDSOURCING SYSTEMS." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1511.

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A pressing need for efficient personalized recommendations has emerged in crowdsourcing systems. On the one hand, workers confront a flood of tasks, and they often spend too much time to find tasks matching their skills and interests. Thus, workers want effective recommendation of the most suitable tasks with regard to their skills and preferences. On the other hand, requesters sometimes receive results in low-quality completion since a less qualified worker may start working on a task before a better-skilled worker may get hands on. Thus, requesters want reliable recommendation of the best wo
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Yang, Dingqi. "Understanding human dynamics from large-scale location-centric social media data : analysis and applications." Thesis, Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0002/document.

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La dynamique humaine est un sujet essentiel de l'informatique centrée sur l’homme. Elle se concentre sur la compréhension des régularités sous-jacentes, des relations, et des changements dans les comportements humains. En analysant la dynamique humaine, nous pouvons comprendre non seulement des comportements individuels, tels que la présence d’une personne à un endroit précis, mais aussi des comportements collectifs, comme les mouvements sociaux. L’exploration de la dynamique humaine permet ainsi diverses applications, entre autres celles des services géo-dépendants personnalisés dans des scén
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Yang, Dingqi. "Understanding human dynamics from large-scale location-centric social media data : analysis and applications." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0002.

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La dynamique humaine est un sujet essentiel de l'informatique centrée sur l’homme. Elle se concentre sur la compréhension des régularités sous-jacentes, des relations, et des changements dans les comportements humains. En analysant la dynamique humaine, nous pouvons comprendre non seulement des comportements individuels, tels que la présence d’une personne à un endroit précis, mais aussi des comportements collectifs, comme les mouvements sociaux. L’exploration de la dynamique humaine permet ainsi diverses applications, entre autres celles des services géo-dépendants personnalisés dans des scén
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7

Östlin, Erik. "On Radio Wave Propagation Measurements and Modelling for Cellular Mobile Radio Networks." Doctoral thesis, Karlskrona : Blekinge Institute of Technology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00443.

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To support the continuously increasing number of mobile telephone users around the world, mobile communication systems have become more advanced and sophisticated in their designs. As a result of the great success with the second generation mobile radio networks, deployment of the third and development of fourth generations, the demand for higher data rates to support available services, such as internet connection, video telephony and personal navigation systems, is ever growing. To be able to meet the requirements regarding bandwidth and number of users, enhancements of existing systems and
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8

Arrascue, Ayala Victor Anthony [Verfasser], and Georg [Akademischer Betreuer] Lausen. "Towards an effective consumption of large-scale knowledge graphs for recommendations." Freiburg : Universität, 2020. http://d-nb.info/1223366189/34.

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9

Ardekani, Kamyar. "Feature Recommender : a large-scale in-situ study of proactive software feature recommendations." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/59761.

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In this thesis, we describe our design of Feature Recommender, a Mozilla Firefox browser extension, which proactively recommends features that it predicts will benefit users based on their individual usage behaviors. The goal of these pop-up notifications is to help users discover new features. How to maximize the effectiveness of such notifications while minimizing user interruptions remains a difficult open problem. One approach is to carefully time when the notifications are delivered. In our deployment of Feature Recommender, we study the effect of two delivery timing parameters: delivery
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10

Richardson, James Rutherford. "Accommodating existing settlements in large scale development : recommendations for Sha Tin New Town Hong Kong." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/69533.

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MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH.<br>Thesis (M. Arch.)--Massachusetts Institute of Technology, Dept. of Architecture; and, (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1981.<br>Bibliography: leaves 173-176.<br>by James Rutherford Richardson, IV.
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11

Tavares, Antonio Vanderlei. "Avaliação de larga escala: resultados e tomada de decisão." Pontifícia Universidade Católica de São Paulo, 2012. https://tede2.pucsp.br/handle/handle/16037.

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Made available in DSpace on 2016-04-28T20:56:30Z (GMT). No. of bitstreams: 1 Antonio Vanderlei Tavares.pdf: 584517 bytes, checksum: 338414fd05f955f86db1005d6ab0bd33 (MD5) Previous issue date: 2012-06-14<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>This study aimed to identify and analyze recommendations and decisions from the large-scale assessment of a system of private education in the state of Sao Paulo. The methodological trajectory, initially, there were readings of the final reports of large-scale assessments to identify and document the recommendations and decisio
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12

Draidi, Fady. "Recommandation Pair-à-Pair pour Communautés en Ligne à Grande Echelle." Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2012. http://tel.archives-ouvertes.fr/tel-00766963.

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Les systèmes de recommandation (RS) et le pair-à-pair (P2) sont complémen-taires pour faciliter le partage de données à grande échelle: RS pour filtrer et person-naliser les requêtes des utilisateurs, et P2P pour construire des systèmes de partage de données décentralisés à grande échelle. Cependant, il reste beaucoup de difficultés pour construire des RS efficaces dans une infrastructure P2P. Dans cette thèse, nous considérons des communautés en ligne à grande échelle, où les utilisateurs notent les contenus qu'ils explorent et gardent dans leur espace de travail local les contenus de qualité
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13

Kun-FaLin and 林崑發. "Exploiting an Incremental SVD-based Scheme for Large-scale Recommendation Systems." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/59897143168919026531.

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14

Chien, John C. "Apply Feature Extraction, SVM and LSA to Analyze Large-Scale Data for Recommendation Systems." 2008. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0020-1308200813355700.

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15

Chien, John C., and 簡健宇. "Apply Feature Extraction, SVM and LSA to Analyze Large-Scale Data for Recommendation Systems." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/51561654694589402620.

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碩士<br>國立暨南國際大學<br>資訊工程學系<br>96<br>Recommendation systems based on collaborative filtering predict customer preference for items by learning the customer-item pairs of the past. A predominant approach to collaborative filtering is neighborhood based (KNN-based), where the customer-item preference rating is discovered from ratings of similar items or customers. In this research work, we apply latent semantic analysis of IR to discover relation densities between customers and items. Unlike previous approaches, this method does not require system to perform exhaustive search for association rules
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16

Fuller, Amanda Beth. "Large-scale prairie restoration four case studies and recommendations for the Badger Army Ammunition Plant /." 2002. http://catalog.hathitrust.org/api/volumes/oclc/50083823.html.

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Thesis (M.S.)--University of Wisconsin--Madison, 2002.<br>Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (p. 159-171).
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17

Maas, Bea. "Birds, bats and arthropods in tropical agroforestry landscapes: Functional diversity, multitrophic interactions and crop yield." Doctoral thesis, 2013. http://hdl.handle.net/11858/00-1735-0000-0022-5E77-5.

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