[PDF] Top 20 Group recommendation strategies based on collaborative filtering
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Group recommendation strategies based on collaborative filtering
... 2.4.1 Recommending for groups using collaborative filtering We can pose the problem of recommendations for groups in the domain of recommender systems in the following way: How to sugges[r] ... See full document
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Taxonomy-driven content-based recommendation for new itens
... Collaborative filtering (CF) algorithms are generally reported to have the best accuracy in traditional recommendation scenarios [Cremonesi et ...item recommendation problem [Adomavicius and ... See full document
61
An Improved Collaborative Filtering Recommendation Algorithm Combining Item Clustering and Slope One Scheme
... improved recommendation algorithm that combines item clustering and weighted slope one ...Density Based Spatial Clustering of Applications with Noise (DBSCAN) [5] clustering algorithm to partition the set ... See full document
4
Recomendação de música: comparação entre collaborative filtering e context filtering
... well-known Collaborative Filtering technique generates recommendations based on the interests of users with similar ...in recommendation systems and increased user satisfaction has been ... See full document
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Recomendação de Objetos de Aprendizagem utilizando Filtragem Colaborativa baseada em Tendências e em Estilos de Aprendizagem / Learning Object Recommendation Using Collaborative Filtering Based on Learning Styles and Trends
... Nesta pesquisa, é proposta uma estratégia de recomendação personalizada referente a Objetos de Aprendizagem, com base nos Estilos de Aprendizagem dos estudantes e na Filtra[r] ... See full document
14
Collaborative filtering for brain-computer interaction using transfer learning and active class selection.
... with group or normative data, in practice this tends to result in significantly lower performance than calibrating with individual data ...reality based Stroop task [6], which has been shown to have high ... See full document
18
Automatic Query expansion based on tag recommendation
... are based on pseudo-relevance ...found on the Web, such as on-line encyclopedias and collaborative social annotation systems, to select seman- tically rich expansion ...automatically ... See full document
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Conglomeration of Instance Filtering’s k- Nearest Neighborhood and Collaborative Filtering’s Item based Recommendation on Airline Dataset System using Map-Reduce and Mahout
... implemented on top of Apache Hadoop and MapReduce ...developer: collaborative filtering algorithms, data clustering, and data ...explore collaborative filtering technique using Pearson ... See full document
8
Research on Personalized Recommendation in E-commerce Service based on Data Mining
... made on the basis of the dual informat ion fro m the both source: a similar-user group and an e xpert-user ...xpert-based collaborative filtering approach, in wh ich the e xperts ... See full document
5
The Prediction Approach for Periodontitis Using Collaborative Filtering Method in Big Data
... for collaborative filtering of future Prediction. Previous work on recommender systems typically relies on feedback on a particular attribute of a disease, such as an age, and ... See full document
5
USER RECOMMENDATION ALGORITHM IN SOCIAL TAGGING SYSTEM BASED ON HYBRID USER TRUST
... with Collaborative Tagging ...user. Collaborative Filtering (CF) seems to be the most popular technique in recommender systems to deal with information overload issue but CF suffers from accuracy ... See full document
11
TRIBO: Musical venues recommendation system based on the social web
... big on the United States, being created in the United Kingdom, ...the collaborative based recommendation system, proving that “better algorithms are nice but better data is nicer” (Krause, ... See full document
111
Collaborative Filtering Based Recommendation System: A survey
... Content based, collaborative and hybrid methods were proposed and several industrial-strength systems have been ...of collaborative filtering is that recommendations for a new user are ... See full document
18
Recommender systems as “tastemakers”: Collaborative filtering as a market strategy for online cultural products
... studies based on experiments and statistical data in order to specify the degree of influence such systems hold in determining cultural preferences and practices and to compare the credibility and value of ... See full document
14
Recommending Recommender Systems: tackling the Collaborative Filtering algorithm selection problem
... multiple recommendation strategies in an attempt to overcome the problems that each strategy poses by using positive functionalities from ...CBF strategies ( Bobadilla et ...hybridization ... See full document
196
Pre-processing approaches for collaborative filtering based on hierarchical clustering
... This work explores the use of hierarchies of clusters, therefore this section is focused on hierarchical clustering approaches. Hierarchies of clusters can be obtained in many ways, for instance one algorithm can ... See full document
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Deployment and evaluation of a usage based collaborative filtering recommendation system with blacklists
... One of the currently most popular means of interaction used by people are social web sites. In these web sites, and in the particular case of Palco Principal (PP), the web site of the company with the same name, users ... See full document
10
E-LEARNING PERSONALIZATION BASED ON COLLABORATIVE FILTERING AND LEARNER’S PREFERENCE
... the collaborative filtering to classify a teaching strategy as “appropriate” or “not appropriate” for the learner ...an On-line phase which uses to collect the user interests from the log files, and ... See full document
17
An Adaptive Learning Based on Ant Colony and Collaborative Filtering
... courses based on preferences and learners abilities, to effectively master the management of knowledge to be ...learning recommendation [4], intelligent learning contents suggestions [8], Adaptive ... See full document
5
Cache strategies for internet-based video on-demand distribution
... is based on a utility function that considers (i) the average number of accesses, (ii) the average duration of accesses, (iii) the length of cached data, and (iv) the expected probability of future ...is ... See full document
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