Recommendations using information from multiple association rules : a probabilistic approach
Year of publication: |
2015
|
---|---|
Authors: | Ghoshal, Abhijeet ; Menon, Syam ; Sarkar, Sumit |
Published in: |
Information systems research : ISR. - Catonsville, MD : INFORMS, ISSN 1047-7047, ZDB-ID 1081934-4. - Vol. 26.2015, 3, p. 532-551
|
Subject: | personalization | Bayesian estimation | maximum likelihood | information theory | data analytics | Bayes-Statistik | Bayesian inference | Theorie | Theory | Wahrscheinlichkeitsrechnung | Probability theory | Maximum-Likelihood-Schätzung | Maximum likelihood estimation | Information |
-
The multivariate split normal distribution and asymmetric principal components analysis
Villani, Mattias, (2004)
-
Accuracy of mortgage portfolio risk forecasts during financial crises
Lee, Yong Woong, (2016)
-
Identification versus misspecification in New Keynesian monetary policy models
Adolfson, Malin, (2019)
- More ...
-
Recommendations Using Information from Multiple Association Rules : A Probabilistic Approach
Ghoshal, Abhijeet, (2021)
-
Hiding sensitive information when sharing distributed transactional data
Ghoshal, Abhijeet, (2020)
-
Modifying transactional databases to hide sensitive association rules
Menon, Syam, (2022)
- More ...