Space: Apache Mahout (https://cwiki.apache.org/confluence/display/MAHOUT)
Page: Powered By Mahout
(https://cwiki.apache.org/confluence/display/MAHOUT/Powered+By+Mahout)
Edited by Emilio Suarez:
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h1. Intro
Are you using Mahout to do Machine Learning? Care to share?
*NOTE: Please add links in alphabetical order. Links here do NOT imply
endorsement by Mahout, its committers or the Apache Software Foundation and are
for informational purposes only.*
h1. Commercial Use
* Adobe AMP uses Mahout's clustering algorithms to increase video consumption
by better user targeting. See
[http://nosql.mypopescu.com/post/2082712431/hbase-and-hadoop-at-adobe]
* Amazon's Personalization Platform -- See
[http://www.linkedin.com/groups/Apache-Mahout-2182513]
* [AOL |http://www.aol.com] use Mahout for shopping recommendations. See
[http://www.slideshare.net/kryton/the-data-layer]
* [Booz Allen Hamilton |http://www.boozallen.com/] uses Mahout's clustering
algorithms. See [http://www.slideshare.net/ydn/3-biometric-hadoopsummit2010]
* [Buzzlogic|http://www.buzzlogic.com] uses Mahout's clustering algorithms to
improve ad targeting
* [Cull.tv|http://cull.tv/] uses modified Mahout algorithms for content
recommendations
* !http://cdn.dataminelab.com/favicon.ico! [DataMine
Lab|http://dataminelab.com] uses Mahout's recommendation and clustering
algorithms to improve our clients' ad targeting.
* [Drupal|http://drupal.org/project/recommender] users Mahout to provide open
source content recommendation solutions.
* [Foursquare|http://www.foursquare.com] uses Mahout for its [recommendation
engine
|http://engineering.foursquare.com/2011/03/22/building-a-recommendation-engine-foursquare-style/].
* [Idealo|http://www.idealo.de] uses Mahout's recommendation engine.
* [InfoGlutton|http://www.infoglutton.com] uses Mahout's clustering and
classification for various consulting projects.
* [Intela|http://www.intela.com/] has implementations of Mahout's
recommendation algorithms to select new offers to send tu customers, as well as
to recommend potential customers to current offers. We are also working on
enhancing our offer categories by using the clustering algorithms. We have a
[blog post|http://intela.com/best-practices/intela-gets-smarter] where we talk
about it.
* !http://ioffer.com/favicon.ico! [iOffer|http://www.ioffer.com] uses Mahout's
Frequent Pattern Mining and Collaborative Filtering to recommend items to users.
* !http://kau.li/favicon.ico! [Kauli|http://kau.li/en], one of Japanese
Adnetwork, uses Mahout's clustering to handle clickstream data for predicting
audience's interests and intents.
* !http://mendeley.com/favicon.ico! [Mendeley|http://mendeley.com] uses Mahout
internally to test collaborative filtering algorithms and as part of their work
on EU and JISC-funded research collaborations.
* !http://mippin.com/favicon.ico! [Mippin|http://mippin.com] uses Mahout's
collaborative filtering engine to recommend news feeds
*
[Mobage|http://www.slideshare.net/hamadakoichi/mobage-prmu-2011-mahout-hadoop]
uses Mahout in their analysis pipeline
* !http://www.newscred.com/media/img/favicon.ico!
[NewsCred|http://platform.newscred.com] uses Mahout to generate clusters of
news articles and to surface the important stories of the day
* !http://blog.radoop.eu/favicon.ico! [Radoop|http://radoop.eu] provides a
drag-n-drop interface for big data analytics, including Mahout clustering and
classification algorithms
* [Sematext|http://www.sematext.com/] uses Mahout for its [Recommendation
Engine|http://www.sematext.com/products/recommendation-engine/index.html]
* [SpeedDate.com|http://www.speeddate.com] uses Mahout's collaborative
filtering engine to recommend member profiles
* [Yahoo\!|http://www.yahoo.com] Mail uses Mahout's Frequent Pattern Set
Mining. See [http://www.slideshare.net/hadoopusergroup/mail-antispam]
* !http://a.imageshack.us/img823/3443/logoyf.gif! [365Media
|http://365media.com/] uses *Mahout's* Classification and Collaborative
Filtering algorithms in its Real-time system named
[UPTIME|http://uptime.365media.com/] and 365Media/Social
h1. Academic Use
* [Dicode|https://www.dicode-project.eu/] project uses Mahout's clustering and
classification algorithms on top of HBase.
* The course [Large Scale Data Analysis and Data
Mining|http://www.dima.tu-berlin.de/menue/studium_und_lehre/aktuelles_semester_sommersemester_2011/aim_3_advanced_information_management]
at [TU Berlin|http://www.tu-berlin.de/] uses Mahout to teach students
about the parallelization of data mining problems with Hadoop and Map/Reduce
* Mahout is used at Carnegie Mellon University, as a comparable platform to
[GraphLab|http://www.graphlab.ml.cmu.edu/].
* The [ROBUST project|http://www.robust-project.eu/], co-funded by the European
Commission, employs Mahout in the large scale analysis of online community data.
* Mahout is used for research and data processing at [Nagoya Institute of
Technology|http://www.nitech.ac.jp/eng/schools/grad/cse.html], in the context
of a large-scale citizen participation platform project, funded by the Ministry
of Interior of Japan.
* Several researches within [Digital Enterprise Research
Institute|http://www.deri.ie] [NUI Galway|http://www.nuigalway.ie] use Mahout
for e.g. topic mining and modelling of large corpora.
* We used Mahout in the NoTube EU project, and it saved a lot of time (and a
brain transplant). The only piece we've used heavily in our apps
(http://vimeo.com/user3487770http://notube.tv/) so far is the Taste
recommender, but I've been digging deeper into the other components. I can't
claim we're a hugely famous or successful application, but I can say without
doubt I don't regret using Mahout. It did what it said it would do, and easily.
One nice thing about this community, is that Mahout is not
over-marketed. If the nature or scale of your problem better suits other tools,
the Mahout folk will tell you so.
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