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  Accurate Recommendations Using Linked Taxonomies of Subjective Assessments  
  Authors : Vaishnavi Pakhode; Advait Pakhode ; Nagesh Jadhav
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Subjective assessments like ‘beautiful’ and ‘breathtaking’ are assigned to items by users and are commonly found in reviews on many online sites. Analyzing the links between these SAs and items can help improve the recommendation accuracy. We propose a different method which links a taxonomy of items to a taxonomy of SAs to capture user’s interests in detail.

 

Published In : IJCSN Journal Volume 4, Issue 3

Date of Publication : June 2015

Pages : 447 - 450

Figures : 02

Tables : --

Publication Link : Accurate Recommendations Using Linked Taxonomies of Subjective Assessments

 

 

 

Vaishnavi Pakhode : MIT College of Engineering, Pune, Maharashtra 411038, India

Advait Pakhode : MIT College of Engineering, Pune, Maharashtra 411038, India

Nagesh Jadhav : MIT College of Engineering, Pune, Maharashtra 411038, India

 

 

 

 

 

 

 

Recommendation System

Collaborative Filtering

Subjective Assessments

In this study, we have implemented a novel method for the measurement of similarity of users. Our method groups the SAs assigned by the users to items in SC and the SAs/SCs reflect the classes in which they are included. Our method computes the similarities of users based on the SAs/SCs assigned to items and those assigned to item classes.

 

 

 

 

 

 

 

 

 

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