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Collaborative filtering
Known as:
Cf
, Collaborative Filter
, Shilling attacks
Collaborative filtering (CF) is a technique used by recommender systems. Collaborative filtering has two senses, a narrow one and a more general one…
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49 relations
Apache Mahout
Apache Spark
Business logic
California Report Card
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Broader (2)
Collaborative software
Collective intelligence
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
A new confidence-based recommendation approach: Combining trust and certainty
F. S. Gohari
,
F. S. Aliee
,
H. Haghighi
Information Sciences
2018
Corpus ID: 23473350
2015
2015
A Multi-dimensional Comparison of Toolkits for Machine Learning with Big Data
Aaron N. Richter
,
T. Khoshgoftaar
,
Sara Landset
,
Tawfiq Hasanin
IEEE International Conference on Information…
2015
Corpus ID: 16123465
Big data is a big business, and effective modeling of this data is key. This paper provides a comprehensive multidimensional…
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2012
2012
Forgetting mechanisms for scalable collaborative filtering
João Vinagre
,
A. Jorge
Journal of the Brazilian Computer Society
2012
Corpus ID: 10054248
Collaborative filtering (CF) has been an important subject of research in the past few years. Many achievements have been made in…
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Highly Cited
2011
Highly Cited
2011
Text Text Revolution: A Game That Improves Text Entry on Mobile Touchscreen Keyboards
Dmitry Rudchenko
,
Tim Paek
,
Eric Badger
International Conference on Pervasive Computing
2011
Corpus ID: 2176475
Mobile devices often utilize touchscreen keyboards for text input. However, due to the lack of tactile feedback and generally…
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2011
2011
Mobile commerce product recommendations based on hybrid multiple channels
Duen-Ren Liu
,
Chuen-He Liou
Electronic Commerce Research and Applications
2011
Corpus ID: 8772433
2010
2010
Improving Prediction Accuracy in Trust-Aware Recommender Systems
Sanjog Ray
,
A. Mahanti
Hawaii International Conference on System…
2010
Corpus ID: 28540195
Trust-aware recommender systems are intelligent technology applications that make use of trust information and user personal data…
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2007
2007
Personalized Service System Based on Hybrid Filtering for Digital Library
Fengrong Gao
,
Chunxiao Xing
,
Xiaoyong Du
,
Shan Wang
2007
Corpus ID: 62206922
2006
2006
Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure
Charlie K. Dagli
,
S. Rajaram
,
Thomas S. Huang
ACM International Conference on Image and Video…
2006
Corpus ID: 11044386
Interactively learning from a small sample of unlabeled examples is an enormously challenging task. Relevance feedback and more…
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Highly Cited
2005
Highly Cited
2005
Mining changes in customer buying behavior for collaborative recommendations
Y. Cho
,
Y. Cho
,
S. Kim
Expert systems with applications
2005
Corpus ID: 14347919
2003
2003
Convergent algorithms for collaborative filtering
J. Kleinberg
,
M. Sandler
ACM Conference on Economics and Computation
2003
Corpus ID: 496575
A collaborative filtering system analyzes data on the past behavior of its users so as to make recommendations --- a canonical…
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