PREA: personalized recommendation algorithms toolkit

نویسندگان

  • Joonseok Lee
  • Mingxuan Sun
  • Guy Lebanon
چکیده

Recommendation systems are important business applications with significant economic impact. In recent years, a large number of algorithms have been proposed for recommendation systems. In this paper, we describe an open-source toolkit implementing many recommendation algorithms as well as popular evaluation metrics. In contrast to other packages, our toolkit implements recent state-of-the-art algorithms as well as most classic algorithms.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Personalized Recommendation Method Based on Improve-Collaborative Filtering Algorithms

Collaborative filtering recommender technology is also known as user-oriented recommendation techniques, is currently the most successful personalized recommendation. This paper describes the collaborative filtering recommendation techniques, collaborative filtering recommendation of three steps, and generation of a neighbor recommended. The traditional collaborative filtering algorithm has bee...

متن کامل

A method for evaluating discoverability and navigability of recommendation algorithms

Recommendations are increasingly used to support and enable discovery, browsing, and exploration of items. This is especially true for entertainment platforms such as Netflix or YouTube, where frequently, no clear categorization of items exists. Yet, the suitability of a recommendation algorithm to support these use cases cannot be comprehensively evaluated by any recommendation evaluation meas...

متن کامل

A Method for Evaluating the Navigability of Recommendation Algorithms

Recommendations are increasingly used to support and enable discovery, browsing and exploration of large item collections, especially when no clear classification of items exists. Yet, the suitability of a recommendation algorithm to support these use cases cannot be comprehensively evaluated by any evaluation measures proposed so far. In this paper, we propose a method to expand the repertoire...

متن کامل

Study on Personalized Course Generation Based on Layered Recommendation Algorithm

The paper introduces the concept of a layered recommendation system (LRS) based on multi-dimensional feature vectors to implement personalized course generation model and algorithms. In this work, we present a personalized course generation algorithm based on the multi-dimensional feature vectors (PCG-LRS) and hybrid applications by content-based recommendations and collaborative filtering reco...

متن کامل

An Interactive Personalized Recommendation System Using the Hybrid Algorithm Model

With the rapid development of e-commerce, the contradiction between the disorder of business information and customer demand is increasingly prominent. This study aims to make ecommerce shopping more convenient, and avoid information overload, by an interactive personalized recommendation system using the hybrid algorithm model. The proposed model first uses various recommendation algorithms to...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Journal of Machine Learning Research

دوره 13  شماره 

صفحات  -

تاریخ انتشار 2012