Mahout — 3 Technical Articles

Jun 11, 2016 · Artificial Intelligence

Designing System & Personalized Recommendations Using Mahout

This article outlines the design of both system-wide and personalized recommendation modules for e‑commerce platforms, explains three recommendation approaches (demographic, content‑based, collaborative filtering), details the implementation of Mahout’s collaborative‑filtering algorithm with Java code, discusses data sources, technology stack, algorithm choices, and solutions to the cold‑start problem.

Mahoutcollaborative filteringe-commerce

0 likes · 14 min read

Designing System & Personalized Recommendations Using Mahout

21CTO

Apr 12, 2016 · Artificial Intelligence

Designing System and Personalized Recommendation Engines with Mahout and Spark

This article explains the architecture of both system-wide and personalized recommendation modules, compares three recommendation strategies, details the use of Apache Mahout for collaborative filtering with Java code examples, and discusses cold‑start solutions within a Spark‑Hadoop stack.

MahoutSparkcold start

0 likes · 15 min read

Designing System and Personalized Recommendation Engines with Mahout and Spark

21CTO

Oct 24, 2015 · Artificial Intelligence

Building an Offline Recommendation System with Mahout: Practical Steps and Tips

This article walks through the end‑to‑end process of building an offline recommendation system using Mahout, covering data collection, filtering, storage, various collaborative‑filtering algorithms, similarity measures, evaluation metrics, parameter tuning, AB testing, and spam‑fighting strategies.

Mahoutcollaborative filteringmachine learning

0 likes · 16 min read

Building an Offline Recommendation System with Mahout: Practical Steps and Tips