Open problems in recommender systems diversity
Nitin Sodera, Akshi Kumar
Abstract
Nitin Sodera, Akshi Kumar
Abstract
With increasing information available online, requirement for accurate information filtering tools/ information retrieval have become necessary. Recommender systems have been a crucial research subject after the inclusion of the very first paper on filtering. Recommender Systems is a tool that provides recommendations for products/services which maybe of liking to a particular consumer. Despite the fact that research on recommender systems has extended extensively over the last decades, there's still requirement in the complete literature evaluation of the research made till date and classification of Recommender Systems. This paper presents a categorical review and provides a survey on the diversity & techniques of Recommender systems. The open problems in the area are pinpointed and mapped to the respective recommendation paradigm type thus giving an insight to the research trends in the field of recommender system. The intent of this work is to serve as a base literature review to beginners and at the same time aid as an important pertinent survey for identifying the opportunities in thearea.
OpenAlex reports 8 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
With increasing information available online, requirement for accurate information filtering tools/ information retrieval have become necessary. Recommender systems have been a crucial research subject after the inclusion of the very first paper on filtering. Recommender Systems is a tool that provides recommendations for products/services which maybe of liking to a particular consumer. Despite the fact that research on recommender systems has extended extensively over the last decades, there's still requirement in the complete literature evaluation of the research made till date and classification of Recommender Systems. This paper presents a categorical review and provides a survey on the diversity & techniques of Recommender systems. The open problems in the area are pinpointed and mapped to the respective recommendation paradigm type thus giving an insight to the research trends in the field of recommender system. The intent of this work is to serve as a base literature review to beginners and at the same time aid as an important pertinent survey for identifying the opportunities in thearea.
Key concepts: Recommender system, Computer science, Categorical variable, Field (mathematics), Information retrieval, Collaborative filtering, World Wide Web, Diversity (politics)