Proceedings ArticleDOI
Evaluation criteria for measuring the performance of recommender systems
Ruchika,Ajay Vikram Singh,Dolly Sharma +2 more
- pp 1-6
Reads0
Chats0
TLDR
An insight is given into various types of filtering techniques associated with recommender systems and the problems faced and evaluation criteria on the basis of which various algorithms made for recommendation purpose can be compared.Abstract:
The explosive growth of social network with the help of e-commerce websites has made the issue of information retrieval increasingly challenging. Users may not have the time or knowledge to personally evaluate the options which are available on social network platform. Recommender systems present themselves as a practical answer to endless options available online. In this research paper, we give an insight into various types of filtering techniques associated with recommender systems. We also discuss the problems faced by these filtering techniques and evaluation criteria on the basis of which various algorithms made for recommendation purpose can be compared. Finally we propose a composite news recommendation system model.read more
Citations
More filters
Proceedings ArticleDOI
Building an effective recommender system using machine learning based framework
TL;DR: This paper has shown adaption of collaborative filtering in Apache Mahout platforms via Eclipse on a sample data set and shown how this affects day to day lives.
Proceedings ArticleDOI
Decision Making Support System for Prediction of Prices in Agricultural Commodity
TL;DR: A new framework for decision making support model for prediction of prices in agricultural commodities is proposed and techniques of data mining in agriculture are included that will help the farmers to predict the agricultural commodity prices.
Proceedings ArticleDOI
ERP Implementation in the Oil and Gas Sector: A Case Study in Sultanate of Oman
TL;DR: The study suggests that Oil and Gas industries should implement ERP system to improve the efficiency and productivity of this sector and boost its growth in all aspects.
Proceedings ArticleDOI
Impact of social media on society in a large and specific to teenagers
TL;DR: This paper reviews social media, society and business, and how social media impact teenagers, and shows by RSA that the rate of cybercrime reached 173% by mobile phones during the period 2013–2015.
Proceedings ArticleDOI
Business Intelligence Development by Analysing Customer Sentiment
TL;DR: In real life it is often found that a particular attribute is present in VDWs that is missing in actual data warehouse, so the system needs to decide whether the attribute will be added in to physical data warehouse or not.
References
More filters
Journal ArticleDOI
Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
TL;DR: This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches.
Proceedings ArticleDOI
Item-based collaborative filtering recommendation algorithms
TL;DR: This paper analyzes item-based collaborative ltering techniques and suggests that item- based algorithms provide dramatically better performance than user-based algorithms, while at the same time providing better quality than the best available userbased algorithms.
Journal ArticleDOI
Hybrid Recommender Systems: Survey and Experiments
TL;DR: This paper surveys the landscape of actual and possible hybrid recommenders, and introduces a novel hybrid, EntreeC, a system that combines knowledge-based recommendation and collaborative filtering to recommend restaurants, and shows that semantic ratings obtained from the knowledge- based part of the system enhance the effectiveness of collaborative filtering.
Book ChapterDOI
Introduction to Recommender Systems Handbook
TL;DR: The main goal is to delineate, in a coherent and structured way, the chapters included in this handbook and to help the reader navigate the extremely rich and detailed content that the handbook offers.
The Netflix Prize
James Bennett,Stan Lanning +1 more
TL;DR: Netflix released a dataset containing 100 million anonymous movie ratings and challenged the data mining, machine learning and computer science communities to develop systems that could beat the accuracy of its recommendation system, Cinematch.