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Title:Customized ranking by user preference using LRR model
Author(s):Chiang, Bo-Yu
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Latent Aspect Rating Analysis (LARA)
Recommendation system
Abstract:In this thesis, we proposed a customized ranking system that can rank all the entities given a specific user preference. Rank entities by user’s preference is an inevitable strategy of saving user’s time browsing and extracting useful information from Internet. Modern websites always rank these entities by a single numeric value computed by averaging overall rating, but this ranking scheme is of limited use to users. With di↵erent aspect preference, it is obvious that the restaurants ranking should be di↵erent based on their famous features, e.g., service, environment, price. We used the LRR (Latent Rating Regression) model to aggregate restaurants aspect score and proposed two ranking approaches. The experiment results show that the two ranking approaches are both better than the baseline ranking approach.
Issue Date:2015-04-24
Rights Information:Copyright 2015 Bo Yu Chiang
Date Available in IDEALS:2015-07-22
Date Deposited:May 2015

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