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Item-item collaborative filtering
Item-item collaborative filtering, or item-based, or item-to-item, is a form of collaborative filtering based on the similarity between items…
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8 relations
Collaborative filtering
MovieLens
Overfitting
Recommender system
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
A Genre-Based Item-Item Collaborative Filtering: Facing the Cold-Start Problem
S. Barman
,
M. Hasan
,
F. Roy
ICSCA
2019
Corpus ID: 153314117
Recommender System is a technique which is used to recommend an item or product to a user based on the user's preference…
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2019
2019
Estimating Confidence of Individual User Predictions in Item-based Recommender Systems
Cesare Bernardis
,
Maurizio Ferrari Dacrema
,
P. Cremonesi
UMAP
2019
Corpus ID: 182952077
This paper focuses on recommender systems based on item-item collaborative filtering (CF). Although research on item-based…
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2018
2018
Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering
Guy Bresler
,
Mina Karzand
Information Theory and Applications Workshop (ITA…
2018
Corpus ID: 362026
We consider an online model for recommendation systems, with each user being recommended an item at each time-step and providing…
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Review
2018
Review
2018
BEP TI3806
J. Katzy
,
T. Rietveld
,
+6 authors
B. V. Riemsdijk
2018
Corpus ID: 52830537
As Machine Learning is becoming more accessible to small businesses, thanks to the rapid advance in computing power, smaller…
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2018
2018
Eigenvalue analogy for confidence estimation in item-based recommender systems
Maurizio Ferrari Dacrema
,
P. Cremonesi
ArXiv
2018
Corpus ID: 52167420
Item-item collaborative filtering (CF) models are a well known and studied family of recommender systems, however current…
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2016
2016
Collaborative Filtering with Low Regret
Guy Bresler
,
D. Shah
,
L. F. Voloch
SIGMETRICS
2016
Corpus ID: 3655493
There is much empirical evidence that item-item collaborative filtering works well in practice. Motivated to understand this, we…
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2015
2015
Regret Guarantees for Item-Item Collaborative Filtering
Guy Bresler
,
D. Shah
,
L. F. Voloch
2015
Corpus ID: 18466079
There is much empirical evidence that item-item collaborative filtering works well in practice. Motivated to understand this, we…
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2015
2015
Group Recommender Systems: Combining User-User and Item-Item Collaborative Filtering Techniques
Abinash Pujahari
,
V. Padmanabhan
International Conference on Information…
2015
Corpus ID: 8379898
Recommender Systems, these days, are no longer personal recommender systems, rather they are group recommender systems which list…
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Highly Cited
2015
Highly Cited
2015
Letting Users Choose Recommender Algorithms: An Experimental Study
Michael D. Ekstrand
,
Daniel Kluver
,
F. M. Harper
,
J. Konstan
RecSys
2015
Corpus ID: 3065090
Recommender systems are not one-size-fits-all; different algorithms and data sources have different strengths, making them a…
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2013
2013
Application of Using Simulated Annealing to Combine Clustering with Collaborative Filtering for Item Recommendation
Z. Feng
,
Y. Su
2013
Corpus ID: 62672512
tem-item collaborative filtering was widely used in item recommender system because of good recommend effects. However when…
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