Litcius/Paper detail

A Literature Review of Recommendation Systems

Kushan Bhareti, Shevon Perera, Shehan Jamal, Manul Hiyare Pallege, Vishma Akash, Sihan Wiieweera

20202020 IEEE International Conference for Innovation in Technology (INOCON)14 citationsDOI

Abstract

Recommendation Systems (RS) are tools that recommend items to be viewed by users. While these tools have gained popularity since the 1990s they can be found in most applications on the internet nowadays to perform recommendations to users in order to sustain and increase the interactivity within the applications. RS come in different forms that approach the task of making recommendations in different ways. These techniques have evolved over the years and can be found to be conducted using both complex and simple algorithms. While there are many algorithms that perform recommendations different algorithms can prove to be more sustainable for different tasks. This paper reviews a number of simple and complex algorithms that are used for recommendation and discuss their applications and their advantages and disadvantages.

Topics & Concepts

PopularityComputer scienceInteractivityRecommender systemSimple (philosophy)Task (project management)The InternetOrder (exchange)Data scienceWorld Wide WebEngineeringSystems engineeringPhilosophyFinanceSocial psychologyPsychologyEconomicsEpistemologyRecommender Systems and TechniquesAdvanced Bandit Algorithms ResearchData Stream Mining Techniques