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Relational Collaborative Topic Regression for Recommender Systems
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Relational Collaborative Topic Regression for Recommender Systems

Category : Data Mining


Sub Category : JAVA


Project Code : ITJDM07


Project Abstract

Relational Collaborative Topic Regression for Recommender  Systems

 

ABSTRACT

 

In this project, we develop a novel hierarchical Bayesian model called Relational Collaborative Topic Regression (RCTR), which extends CTR by seamlessly integrating the user-item feedback information, item content information, and network structure among items into the same model. Typically, the feedback matrix is sparse, which means that most items are given feedback by few users or most users only give feedback to few items. Due to this sparsity problem, traditional with only feedback information will suffer from unsatisfactory performance. More specifically, it is difficult for CF methods to achieve good performance in both item-oriented setting and user-oriented setting when the feedback matrix is sparse. In an item-oriented setting where we need to recommend users to items, it is generally difficult to know which users could like an item if it has only been given feedback by one or two users.

 

 

EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

Collaborative topic regression (CTR) is one of these methods which has achieved promising performance by successfully integrating both feedback information and item content information.

More specifically, it is difficult for CF methods to achieve good performance in both item-oriented setting and user-oriented setting when the feedback matrix is sparse

PROPOSED CONCEPT: -

 Relational Collaborative Topic Regression (RCTR), which extends CTR by seamlessly integrating the user-item feedback information

We develop a novel hierarchical Bayesian model called Relational Collaborative Topic Regression (RCTR), which extends CTR by seamlessly integrating the user-item feedback information, item content information, and network structure among items into the same model.

EXISTING TECHNIQUE:-

Collaborative topic regression (CTR)

PROPOSED TECHNIQUE:-

Relational Collaborative Topic Regression (RCTR)

TECHNIQUE DEFINITION:-

 Collaborative topic regression (CTR) which jointly models the user-item feedback matrix and the item content information. CTR seamlessly incorporates topic modeling with CF to improve the performance and interpretability.

TECHNIQUE DEFINITION:-

 By extending CTR, RCTR seamlessly integrates the user-item feedback information, item content information and relational (network) structure among items into a principled hierarchical Bayesian model.

DRAWBACKS:-

Less accuracy

Less Performance

 

ADVANTAGES:-

High accuracy

High performance

 

 

 

 

 
 
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