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A literature review and classification of recommender systems research
DH Park, HK Kim, IY Choi, JK Kim - Expert systems with applications, 2012 - Elsevier
Recommender systems have become an important research field since the emergence of
the first paper on collaborative filtering in the mid-1990s. Although academic research on …
the first paper on collaborative filtering in the mid-1990s. Although academic research on …
Conceptualising electronic word of mouth activity: An input‐process‐output perspective
YYY Chan, EWT Ngai - Marketing Intelligence & Planning, 2011 - emerald.com
Purpose–In light of the growth of internet usage and its important role in the field of e‐
commerce, electronic word‐of‐mouth (eWOM) has been changing people's behavior and …
commerce, electronic word‐of‐mouth (eWOM) has been changing people's behavior and …
Factors influencing Internet shop** value and customer repurchase intention
This research empirically examines the effect of various Internet shop** site qualities on
the utilitarian and hedonic values of Internet shop**. The influence of the perceived level …
the utilitarian and hedonic values of Internet shop**. The influence of the perceived level …
Retail business analytics: Customer visit segmentation using market basket data
Basket analytics is a powerful tool in the retail context for acquiring knowledge about
consumer shop** habits and preferences. In this paper, we propose a business analytics …
consumer shop** habits and preferences. In this paper, we propose a business analytics …
Combination of machine learning algorithms for recommendation of courses in E-Learning System based on historical data
Data mining is the process which is used to analyze the large database to find the useful
pattern. Data mining can be used to learn about student's behavior from data collected using …
pattern. Data mining can be used to learn about student's behavior from data collected using …
A recommender system using GA K-means clustering in an online shop** market
The Internet is emerging as a new marketing channel, so understanding the characteristics
of online customers' needs and expectations is considered a prerequisite for activating the …
of online customers' needs and expectations is considered a prerequisite for activating the …
Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations
Collaborative filtering (CF)-based recommender systems represent a promising solution for
the rapidly growing mobile music market. However, in the mobile Web environment, a …
the rapidly growing mobile music market. However, in the mobile Web environment, a …
Application of Web usage mining and product taxonomy to collaborative recommendations in e-commerce
The rapid growth of e-commerce has caused product overload where customers on the Web
are no longer able to effectively choose the products they are exposed to. To overcome the …
are no longer able to effectively choose the products they are exposed to. To overcome the …
[PDF][PDF] A personalized e-learning material recommender system
J Lu - International conference on information technology and …, 2004 - opus.lib.uts.edu.au
Erlearning environments are mainly based on a range of delivery and interactive services.
Web-based personalized learning recommender systems can, as a kind of services in e …
Web-based personalized learning recommender systems can, as a kind of services in e …