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 taxonomy of items to a taxonomy of SAs to capture user’s
interests in detail.
Advait Pakhode : MIT College of Engineering,
Pune, Maharashtra 411038, India
Vaishnavi Pakhode : MIT College of Engineering,
Pune, Maharashtra 411038, India
Nagesh Jadhav : MIT College of Engineering,
Pune, Maharashtra 411038, India
Apoorva Chaudhary : MIT College of Engineering,
Pune, Maharashtra 411038, India
Recommendation System
Collaborative
Filtering
Subjective Assessments
In this study we have explored a novel method that links
taxonomy of items to taxonomy of SAs to improve
measurement of the similarity of user’s interests. 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.
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