Results 1 - 10 of 6,198

MATRIX FACTORIZATION TECHNIQUES FOR RECOMMENDER SYSTEMS

by Yehuda Koren, Robert Bell, Chris Volinsky - IEEE COMPUTER , 2009
"... As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest-neighbor techniques for producing product recommendations, allowing the incorporation of additional information such as implicit feedback, temporal effects, and confidence levels. Modern co ..."
Abstract - Cited by 593 (4 self) - Add to MetaCart
. Therefore, more retailers have become interested in recommender systems, which analyze patterns of user interest in products to provide personalized recommendations that suit a user’s taste. Because good personalized recommendations can add another dimension to the user experience, e-commerce leaders like

Research Article Virtual Goods Recommendations in Virtual Worlds

by Kuan-yu Chen, Hsiu-yu Liao, Jyun-hung Chen, Duen-ren Liu
"... Copyright © 2015 Kuan-Yu Chen et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Virtual worlds (VWs) are computer-simulated envir ..."
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intention. Our research highlights the importance of social interactions in virtual goods recommendation. The experiment’s data were retrieved from an online VW platform, and the results show that the proposed method, considering social interactions and social life circle, has better performance than

Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews

by Peter Turney , 2002
"... This paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (thumbs down). The classification of a review is predicted by the average semantic orientation of the phrases in the review that contain adjectives or adverbs. A ..."
Abstract - Cited by 784 (5 self) - Add to MetaCart
This paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (thumbs down). The classification of a review is predicted by the average semantic orientation of the phrases in the review that contain adjectives or adverbs

Review Of The Satisfaction With Life Scale

by William Pavot, Ed Diener , 2009
"... The Satisfaction With Life Scale (SWLS) was developed to assess satis-faction with the respondent’s life as a whole. The scale does not assess satisfaction with life domains such as health or finances but allows subjects to integrate and weight these domains in whatever way they choose. Normative d ..."
Abstract - Cited by 1557 (12 self) - Add to MetaCart
data are presented for the scale, which shows good convergent validity with other scales and with other types of assessments of subjective well-being. Life satisfaction as assessed by the SWLS shows a degree of temporal stability (e.g., 0.54 for 4 years), yet the SWLS has shown sufficient sensitivity

Content-Boosted Collaborative Filtering for Improved Recommendations

by Prem Melville, Raymond J. Mooney, Ramadass Nagarajan - in Eighteenth National Conference on Artificial Intelligence , 2002
"... Most recommender systems use Collaborative Filtering or Content-based methods to predict new items of interest for a user. While both methods have their own advantages, individually they fail to provide good recommendations in many situations. Incorporating components from both methods, a hybrid rec ..."
Abstract - Cited by 326 (3 self) - Add to MetaCart
Most recommender systems use Collaborative Filtering or Content-based methods to predict new items of interest for a user. While both methods have their own advantages, individually they fail to provide good recommendations in many situations. Incorporating components from both methods, a hybrid

Expertise Recommender: A Flexible Recommendation System and Architecture

by David W. McDonald, Mark S. Ackerman - IN: PROCEEDINGS OF THE 2000 ACM CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK , 2000
"... Locating the expertise necessary to solve difficult problems is a nuanced social and collaborative problem. In organizations, some people assist others in locating expertise by making referrals. People who make referrals fill key organizational roles that have been identified by CSCW and affiliated ..."
Abstract - Cited by 178 (8 self) - Add to MetaCart
the technical aspects of providing good recommendations from social and collaborative concerns.

On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach

by Steven L. Salzberg, Usama Fayyad - Data Mining and Knowledge Discovery , 1997
"... Abstract. An important component of many data mining projects is finding a good classification algorithm, a process that requires very careful thought about experimental design. If not done very carefully, comparative studies of classification and other types of algorithms can easily result in stati ..."
Abstract - Cited by 224 (0 self) - Add to MetaCart
Abstract. An important component of many data mining projects is finding a good classification algorithm, a process that requires very careful thought about experimental design. If not done very carefully, comparative studies of classification and other types of algorithms can easily result

Getting to scale with good educational practice

by Richard F. Elmore - Harvard Educational Review , 1996
"... How can good educational practice move beyond pockets of excellence to reach a much greater proportion of students and educators? While many children and young adults in school districts and communities around the country have long benefited from the tremendous accomplishments of successful teachers ..."
Abstract - Cited by 206 (1 self) - Add to MetaCart
efforts, under current conditions, will be ineffective and transient. He concludes with four detailed recommendations for addressing the issue of scale in improving practice in education. The Problem of Scale in Educational Reform Why do good ideas about teaching and learning have so little impact on U

Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-offit measures

by Karin Schermelleh-engel, Helfried Moosbrugger, Hans Müller - Methods of Psychological Research , 2003
"... For structural equation models, a huge variety of fit indices has been developed. These indices, however, can point to conflicting conclusions about the extent to which a model actually matches the observed data. The present article provides some guide-lines that should help applied researchers to e ..."
Abstract - Cited by 240 (1 self) - Add to MetaCart
-of-fit indices are discussed and some recommendations for practitioners given. Finally, we generated an artificial data set according to a "true" model and analyzed two misspecified and two correctly specified models as examples of poor model fit, adequate fit, and good fit.

Atmospheric Environment

by Jun Wang, Xia Hu, Wenhan Chao, Biyun Hu, Zhoujun Li - Dicarbonyl Products of the OH Radical-Initiated Reactions of Naphthalene and the C1and C2-Alkylnaphthalenes , 2007
"... This paper is concerned with the problem of question recommendation in the setting of Community Question Answering (CQA). Given a question as query, our goal is to rank all of the retrieved questions according to their likelihood of being good recommendations for the query. In this paper, we propose ..."
Abstract - Cited by 215 (10 self) - Add to MetaCart
This paper is concerned with the problem of question recommendation in the setting of Community Question Answering (CQA). Given a question as query, our goal is to rank all of the retrieved questions according to their likelihood of being good recommendations for the query. In this paper, we
Results 1 - 10 of 6,198