Hybrid Recommender Systems: Survey and Experiments

@article{Burke2004HybridRS,
  title={Hybrid Recommender Systems: Survey and Experiments},
  author={R. Burke},
  journal={User Modeling and User-Adapted Interaction},
  year={2004},
  volume={12},
  pages={331-370}
}
  • R. Burke
  • Published 4 November 2002
  • Computer Science
  • User Modeling and User-Adapted Interaction
Recommender systems represent user preferences for the purpose of suggesting items to purchase or examine. [] Key Result Further, we show that semantic ratings obtained from the knowledge-based part of the system enhance the effectiveness of collaborative filtering.
Notice of Violation of IEEE Publication PrinciplesHybrid recommender systems: Survey and experiments
  • V. Vekariya, G. Kulkarni
  • Computer Science
    2012 Second International Conference on Digital Information and Communication Technology and it's Applications (DICTAP)
  • 2012
TLDR
This paper introduces a novel hybrid, system that combines content-based recommendation and collaborative filtering to recommend restaurants, and surveys the landscape of actual and possible hybrid recommenders.
Notice of Violation of IEEE Publication PrinciplesHybrid Recommender Systems: Content-Boosted Collaborative Filtering for Improved Recommendations
  • V. Vekariya, G. Kulkarni
  • Computer Science
    2012 International Conference on Communication Systems and Network Technologies
  • 2012
TLDR
This paper introduces a novel hybrid, a system that combines content boosted recommendation and collaborative Filtering to recommend restaurants, and explains the landscape of actual and possible hybrid recommenders.
An Improved Hybrid Recommender System by Combining Predictions
TLDR
This paper proposes an approach that combines collaborative filtering, content-based and demographic filtering approaches to develop a recommender system for predicting ratings in a dynamic way that achieves good accuracy and high coverage and outperforms the conventional filtering algorithms as well as the naive hybrid methods.
A Survey of Various Hybrid based Recommendation Method
TLDR
The survey of various hybrid filtering to overcome the drawbacks and extensions of a forementioned techniques is consisted of.
A Survey of Various Hybrid based Recommendation Method
TLDR
The survey of various hybrid filtering to overcome the drawbacks and extensions of a forementioned techniques is consisted of.
Survey on Collaborative Filtering, Content-based Filtering and Hybrid Recommendation System
TLDR
An overview of recommender systems that include collaborative filtering, content-based filtering and hybrid approach ofRecommender system is provided.
Ensemble Based Hybrid Recommender Systems
  • Computer Science
  • 2020
TLDR
A weighted average method for combining predictions to improve the accuracy of hybrid models is proposed and used standard error as a measure to assign the weights to the classifiers to approximate their participation in predicting the recommendations.
A Hybrid Based Recommendation System based on Clustering and Association
TLDR
The main aim of this paper is to recommend the best suitable items to the user by cluster the data and applying the association mining over clustering.
Review of Multi Criteria Recommender Systems and its Issues
TLDR
The approaches followed in Collaborative Recommender Systems using multiple criteria ratings are reviewed, issues in this area and extension possibilities are reviewed.
Hybrid Recommender for Research Papers and Articles
TLDR
This research proposed and designed a prototype of a Hybrid recommender called Zira, which is a model that combines both the Collaborative filtering, Content-based filtering, attribute- based approach to look at contextual information as well as an item-based approach that will solve the issues associated with cold-start problems all working concurrently to complement one another.
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Recommendations made by recommender systems can help users navigate through large information spaces of product descriptions, news articles or other items, and are an increasingly important tool in the on-line information and e-commerce burgeon.
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  • Computer Science
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TLDR
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The Wasabi Personal Shopper is a domain-independent database browsing tool designed for on-line information access, particularly for electronic product catalogs, that is compatible with any SQL-accessible catalog.
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