Name
Abstract | ||
|---|---|---|
•All item pair based Bhat_sim similarity model enhances the rating prediction accuracy.•Genetic item order and frequency aware multiparent crossover foster search capability.•Trade-off between precision and topic diversity filters diverse as well as novel items.•NewCrossPMOEA increases mean precision, diversity, and novelty of recommendation list. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2019.112857 | Expert Systems with Applications |
Keywords | Field | DocType |
Recommendation system,Collaborative filtering,Multi-objective optimization,Non-linear similarity,Bhattacharyya coefficient | Recommender system,Bhattacharyya distance,Crossover,Computer science,MovieLens,Popularity,Artificial intelligence,Novelty,RSS,Optimization problem,Machine learning | Journal |
Volume | ISSN | Citations |
139 | 0957-4174 | 1 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ankush Jain | 1 | 4 | 2.48 |
| Pramod Kumar Singh | 2 | 102 | 14.48 |
| Joydip Dhar | 3 | 37 | 12.11 |