Big Data Recommender System

Name: Big Data Recommender System
Brand: LAP Lambert Academic Publishing
SKU: 9786139883646
Price: 789 CZK
Availability: InStock

Autor: Atanas Atanassov, Kamal Al-Barznji

Jazyk:

Vazba: Brožovaná

Vydavatel: LAP Lambert Academic Publishing

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

789 Kč

Recommendation Systems provide the facility to understand a person's taste and find new. As one of t...

Informace o knize

Autor

Atanas Atanassov, Kamal Al-Barznji

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2018

Stránek

EAN

9786139883646

Enbook ID

20155473

Vydavatel

LAP Lambert Academic Publishing

Hmotnost

108

Rozměry

150 x 220 x 4

Kompletní popis

Recommendation Systems provide the facility to understand a person's taste and find new. As one of the most successful approaches to build recommender systems, collaborative filtering (CF) uses the known preferences of a group of users to make recommendations or predictions of the unknown preferences for other users. In this research, we first introduce recommendation systems and CF, then we have proposed a system for generating recommendations on a Big amount of Data by memory based filtering techniques (User-based and Item-based). These techniques require no knowledge of properties of items and characteristics, they only use the information in the rating matrix. We have implemented these recommendation algorithms on Hadoop platform using Apache Mahout, a Machine Learning tool, to provide a scalable system for processing huge data sets efficiently. Finally, we compared and discussed the results of the both techniques to determine their quality of generating recommendations.

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Big Data Recommender System

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