Name
Abstract | ||
|---|---|---|
With current growth of internet sales and content consumption, several research efforts focus on recommendation and personalization approaches as a solution to information overload. In this paper, we first propose a new context-aware recommendation model that inspires from consumption psychology researches. Then, two different techniques for generating recommendations from the proposed model are detailed and evaluated. The first is based on logistic regression and the second uses enumeration in order to calculate the probability a customer purchases a given item. We Also study and evaluate three strategies of recommender systems hybridization based on weighting and selection to eliminate the problems the underlying techniques have when applied solely. At the end, we conclude with some ideas for further development and research. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IS.2012.6335185 | Intelligent Systems |
Keywords | Field | DocType |
Internet,consumer behaviour,electronic commerce,recommender systems,regression analysis,ubiquitous computing,Internet sales,consumption psychology researches,content consumption,context-aware recommendation model,information overload,logistic regression,personalization approaches,recommender systems hybridization | Recommender system,Data modeling,Data mining,Information overload,Weighting,Information retrieval,Consumer behaviour,Computer science,Context model,The Internet,Personalization | Conference |
ISBN | Citations | PageRank |
978-1-4673-2276-8 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohamed Ramzi Haddad | 1 | 9 | 4.98 |
| Hajer Baazaoui Zghal | 2 | 76 | 23.99 |
| Djemel Ziou | 3 | 1395 | 99.40 |
| Henda Ben Ghézala | 4 | 18 | 14.18 |
| Baazaoui, H. | 5 | 0 | 0.34 |
| Ben Ghezala, H. | 6 | 8 | 1.89 |