-
1
-
-
20844435854
-
Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
-
G. Adomavicius and A. Tuzhilin. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 2005.
-
(2005)
IEEE Transactions on Knowledge and Data Engineering
-
-
Adomavicius, G.1
Tuzhilin, A.2
-
3
-
-
0000746402
-
Recommendation as classification: Using social and content-based information in recommendation
-
C. Basu, H. Hirsh, and W. Cohen. Recommendation as classification: using social and content-based information in recommendation. AAAI, 1998.
-
(1998)
AAAI
-
-
Basu, C.1
Hirsh, H.2
Cohen, W.3
-
4
-
-
85161981998
-
Supervised topic models
-
D. Blei and J. McAuliffe. Supervised topic models. NIPS, 2008.
-
(2008)
NIPS
-
-
Blei, D.1
McAuliffe, J.2
-
6
-
-
84860524227
-
Biographies, bollywood, boomboxes and blenders: Domain adaptation for sentiment classification
-
J. Blitzer, M. Dredze, and F. Pereira. Biographies, bollywood, boomboxes and blenders: Domain adaptation for sentiment classification. ACL, 2007.
-
(2007)
ACL
-
-
Blitzer, J.1
Dredze, M.2
Pereira, F.3
-
7
-
-
84865658243
-
How opinions are received by online communities: A case study on amazon.com helpfulness votes
-
C. Danescu-Niculescu-Mizil, G. Kossinets, J. Kleinberg, and L. Lee. How opinions are received by online communities: a case study on amazon.com helpfulness votes. WWW, 2009.
-
(2009)
WWW
-
-
Danescu-Niculescu-mizil, C.1
Kossinets, G.2
Kleinberg, J.3
Lee, L.4
-
8
-
-
52449111462
-
Designing novel review ranking systems: Predicting the usefulness and impact of reviews
-
A. Ghose and P. G. Ipeirotis. Designing novel review ranking systems: predicting the usefulness and impact of reviews. ICEC, 2007.
-
(2007)
ICEC
-
-
Ghose, A.1
Ipeirotis, P.G.2
-
10
-
-
67049164166
-
Collaborative filtering for implicit feedback datasets
-
Y. Hu, Y. Koren, and C. Volinsky. Collaborative filtering for implicit feedback datasets. ICDM, 2008.
-
(2008)
ICDM
-
-
Hu, Y.1
Koren, Y.2
Volinsky, C.3
-
11
-
-
42549096144
-
Opinion spam and analysis
-
N. Jindal and B. Liu. Opinion spam and analysis. WSDM, 2008.
-
(2008)
WSDM
-
-
Jindal, N.1
Liu, B.2
-
12
-
-
0002714543
-
Making large-scale support vector machine learning practical
-
T. Joachims. Making large-scale support vector machine learning practical. Advances in kernel methods, 1999.
-
(1999)
Advances in Kernel Methods
-
-
Joachims, T.1
-
14
-
-
85008044987
-
Matrix factorization techniques for recommender systems
-
Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. IEEE Computer, 2009.
-
(2009)
IEEE Computer
-
-
Koren, Y.1
Bell, R.2
Volinsky, C.3
-
15
-
-
45449086600
-
Low-quality product review detection in opinion summarization
-
J. Liu, Y. Cao, C. Y. Lin, Y. Huang, and M. Zhou. Low-quality product review detection in opinion summarization. EMNLP-CoNLL, 2007.
-
(2007)
EMNLP-CoNLL
-
-
Liu, J.1
Cao, Y.2
Lin, C.Y.3
Huang, Y.4
Zhou, M.5
-
16
-
-
67049169370
-
Modeling and predicting the helpfulness of online reviews
-
Y. Liu, X. Huang, A. An, and X. Yu. Modeling and predicting the helpfulness of online reviews. ICDM, 2008.
-
(2008)
ICDM
-
-
Liu, Y.1
Huang, X.2
An, A.3
Yu, X.4
-
17
-
-
84863117884
-
Graphlab: A new framework for parallel machine learning
-
Y. Low, J. Gonzalez, A. Kyrola, D. Bickson, C. Guestrin, and J. M. Hellerstein. Graphlab: A new framework for parallel machine learning. CoRR, 2010.
-
(2010)
CoRR
-
-
Low, Y.1
Gonzalez, J.2
Kyrola, A.3
Bickson, D.4
Guestrin, C.5
Hellerstein, J.M.6
-
18
-
-
33749244569
-
Content-boosted collaborative filtering for improved recommendations
-
P. Melville, R. J. Mooney, and R. Nagarajan. Content-boosted collaborative filtering for improved recommendations. AAAI, 2002.
-
(2002)
AAAI
-
-
Melville, P.1
Mooney, R.J.2
Nagarajan, R.3
-
21
-
-
72249087537
-
Learning to recommend helpful hotel reviews
-
M. P. O'Mahony and B. Smyth. Learning to recommend helpful hotel reviews. RecSys, 2009.
-
(2009)
RecSys
-
-
O'Mahony, M.P.1
Smyth, B.2
-
22
-
-
83255191401
-
Finding deceptive opinion spam by any stretch of the imagination
-
M. Ott, Y. Choi, C. Cardie, and J. T. Hancock. Finding deceptive opinion spam by any stretch of the imagination. ACL-HLT, 2011.
-
(2011)
ACL-HLT
-
-
Ott, M.1
Choi, Y.2
Cardie, C.3
Hancock, J.T.4
-
23
-
-
80555140075
-
Scikit-learn: Machine learning in python
-
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. Scikit-learn: Machine Learning in Python . JMLR, 2011.
-
(2011)
JMLR
-
-
Pedregosa, F.1
Varoquaux, G.2
Gramfort, A.3
Michel, V.4
Thirion, B.5
Grisel, O.6
Blondel, M.7
Prettenhofer, P.8
Weiss, R.9
Dubourg, V.10
Vanderplas, J.11
Passos, A.12
Cournapeau, D.13
Brucher, M.14
Perrot, M.15
Duchesnay, E.16
-
24
-
-
85030174634
-
Grouplens: An open architecture for collaborative filtering of netnews
-
P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl. Grouplens: an open architecture for collaborative filtering of netnews. CSCW, 1994.
-
(1994)
CSCW
-
-
Resnick, P.1
Iacovou, N.2
Suchak, M.3
Bergstrom, P.4
Riedl, J.5
-
25
-
-
85161989354
-
Probabilistic matrix factorization
-
R. Salakhutdinov. Probabilistic matrix factorization. NIPS, 2008.
-
(2008)
NIPS
-
-
Salakhutdinov, R.1
-
26
-
-
56449131205
-
Bayesian probabilistic matrix factorization using markov chain monte carlo
-
R. Salakhutdinov and A. Mnih. Bayesian probabilistic matrix factorization using markov chain monte carlo. ICML, 2008.
-
(2008)
ICML
-
-
Salakhutdinov, R.1
Mnih, A.2
-
28
-
-
79956023811
-
Distortion as a validation criterion in the identification of suspicious reviews
-
G. Wu, D. Greene, B. Smyth, and P. Cunningham. Distortion as a validation criterion in the identification of suspicious reviews. SOMA, 2010.
-
(2010)
SOMA
-
-
Wu, G.1
Greene, D.2
Smyth, B.3
Cunningham, P.4
-
29
-
-
82555183087
-
Semi-sad: Applying semi-supervised learning to shilling attack detection
-
Z. Wu, J. Cao, B. Mao, and Y. Wang. Semi-sad: applying semi-supervised learning to shilling attack detection. RecSys, 2011.
-
(2011)
RecSys
-
-
Wu, Z.1
Cao, J.2
Mao, B.3
Wang, Y.4
-
30
-
-
70350675904
-
Large-scale parallel collaborative filtering for the netflix prize
-
Y. Zhou, D. Wilkinson, R. Schreiber, and R. Pan. Large-scale parallel collaborative filtering for the netflix prize. AAIM, 2008.
-
(2008)
AAIM
-
-
Zhou, Y.1
Wilkinson, D.2
Schreiber, R.3
Pan, R.4
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