Improving an aggregate recommendation diversity Using ranking-based tactics
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© - September Issue 2013 by IJCTT Journal|
|Volume-4 Issue-9 |
|Year of Publication : 2013|
|Authors :K. Satya Reddy, A. Raghavendra rao|
K. Satya Reddy, A. Raghavendra rao "Improving an aggregate recommendation diversity Using ranking-based tactics"International Journal of Computer Trends and Technology (IJCTT),V4(9):3178-3183 September Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- The importance of Recommender systems is becoming more and more to single users and mluti users by providing personalized recommendations. Many of the algorithms proposed in recommender systems literature have been concentrating on improving the recommendation efficiency rate and other important issues of recommendation quality like diversity of recommendations, etc have been discussed. Trough this paper, we make you aware of various item ranking techniques that will generate recommendations which have considerably higher aggregate diversity over all users while maintaining comparative-levels of recommendation accuracy. Comprehensive empirical evaluation uniformly indicates the diversity in improving the proposed techniques by using several real-world rating datasets and rating prediction algorithms.
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Keywords — : SRAM; Built-In Self-Repair (BISR); Built-In Self Test (BIST); Built-In Address-Analysis (BIAA); Compiler.