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Powered By Apache Mahout

Apache Mahout has powered recommendation, clustering, and classification systems at scale for more than a decade. Today the project builds Qumat, a Python library for writing quantum circuits once and running them on Qiskit, Cirq, or Amazon Braket, and QDP, a GPU-accelerated engine for encoding classical data into quantum states.

See how organizations, developers, and researchers have built with Mahout, and add your own story.

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How Mahout is being used

Use cases the community has shared.

Adobe

User targeting
Adobe logo

Adobe AMP used Mahout's clustering algorithms to increase video consumption through better user targeting.

Source

AOL

Recommendations
AOL logo

AOL used Mahout for shopping recommendations.

Source

Booz Allen Hamilton used Mahout's clustering algorithms for large-scale biometric analysis.

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Drupal

Content recommendation
Drupal logo

The Drupal Recommender API module used Mahout to provide open source content recommendation for Drupal sites.

Foursquare

Recommendations
Foursquare logo

Foursquare used Mahout for its venue recommendation engine.

Source

Intel

Distribution
Intel logo

Intel shipped Mahout as part of its Distribution for Apache Hadoop Software.

LinkedIn

Model training
LinkedIn logo

LinkedIn experimented with Mahout for model training as an alternative to R-based workflows.

LucidWorks

Search and text analytics
LucidWorks logo

LucidWorks Big Data used Mahout for clustering, duplicate document detection, phrase extraction, and classification.

Mendeley

Recommendations
Mendeley logo

Mendeley used Mahout to power Mendeley Suggest, a research article recommendation service.

NewsCred

News clustering
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NewsCred used Mahout to cluster news articles and surface the important stories of the day.

ResearchGate

Recommendations
ResearchGate logo

ResearchGate, the professional network for scientists and researchers, used Mahout's recommendation algorithms.

Sematext

Recommendations
Sematext logo

Sematext used Mahout for its recommendation engine.

Twitter

Topic modeling
Twitter logo

Twitter used Mahout's LDA implementation for user interest modeling.

Yahoo! Mail

Anti-spam
Yahoo! Mail logo

Yahoo! Mail used Mahout's frequent pattern set mining in its anti-spam pipeline.

Source

TU Berlin

Teaching
TU Berlin logo

The Large Scale Data Analysis and Data Mining course at TU Berlin used Mahout to teach students how to parallelize data mining problems.

Nagoya Institute of Technology used Mahout for research and data processing in a large-scale citizen participation platform funded by the Ministry of Interior of Japan.

Researchers at the Digital Enterprise Research Institute used Mahout for topic mining and modelling of large corpora.

Organizations building with Mahout

Companies, projects, and research groups that have told the community they use or have used Apache Mahout.

Using Mahout? Tell the community.

Running Qumat in production, evaluating QDP, teaching a course, publishing research, or still on Mahout Classic? You are part of the story. Open a GitHub issue with the form below and a committer will add you to this page.

Prefer to send the pull request yourself? Add an entry to powered-by.json in the website source.

Disclaimer. Usage information on this page comes from community submissions and publicly available sources such as blog posts, conference talks, and the previous Mahout website. Usage, deployment stage, and other details may change over time. All company names, product names, trademarks, and logos shown here are the property of their respective owners and are used for identification purposes only. Inclusion on this page does not imply endorsement of Apache Mahout by these organizations, nor endorsement of these organizations by the Apache Software Foundation. If you represent an organization listed here and would like your entry or logo updated or removed, please open an issue or email dev@mahout.apache.org.