నైరూప్య

A Survey on Recommender Systems (RSS) and Its Applications

P. N. Vijaya Kumar , Dr. V. Raghunatha Reddy

The growth of the Internet has made it much more difficult to effectively extract useful information from all the available online information. The overwhelming amount of data necessitates mechanisms for efficient information filtering. Recommender systems have the effect of guiding users in a personalized way to interesting objects in a large space of possible options. Recommender Systems (RSs) are software tools and techniques providing suggestions for items to be of use to a user. In this paper we will look at three different recommender system approaches namely Collaborative filtering (CF), Content-based filtering, Hybrid recommender systems that can be used on different e-commerce websites. We briefly describe each type with pros and cons and will present some of the applications of Recommender Systems (RSs) in different domains.

ఇండెక్స్ చేయబడింది

Index Copernicus
Academic Keys
CiteFactor
కాస్మోస్ IF
RefSeek
హమ్దార్డ్ విశ్వవిద్యాలయం
వరల్డ్ కేటలాగ్ ఆఫ్ సైంటిఫిక్ జర్నల్స్
ఇంటర్నేషనల్ ఇన్నోవేటివ్ జర్నల్ ఇంపాక్ట్ ఫ్యాక్టర్ (IIJIF)
ఇంటర్నేషనల్ ఇన్స్టిట్యూట్ ఆఫ్ ఆర్గనైజ్డ్ రీసెర్చ్ (I2OR)
కాస్మోస్

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