Loomia
Encyclopedia
Loomia is a Internet technology company based in San Francisco, California
in the United States. Loomia offers a module that recommends content on a Web site. The company is part of a growing Internet
trend that aims to bridge the gap between technological capabilities and user intents. Loomia's technology analyzes the content on the Web site, as well as user behaviors and social contexts to offer additional content that reflects the user's interests. The technology is reported to find the overlap between these diverse datasets as well as matching it against publisher content preferences. In doing so, Loomia's technology attempts to surface publishers' most valuable content and recommend articles and videos that matter to users.
Loomia has worked with major media companies to optimize their Web site content such as Time.com, The Wall Street Journal
, Forbes
, CNET
, US News & World Report, and others. The content recommendation module can be found on these sites under the header of "People Who Read This Also Read."
Loomia was founded by David Marks, Ken Fromm, and Francis Kelly in 2005.
The company is located in San Francisco, CA.
However, Loomia soon saw other opportunities for their recommendation engine, and Loomia began using their technology to suggest new Web pages to users on content and ecommerce sites While big sites like Amazon have the capital to develop their own recommendation technology, many other publishers don't have the budget for such development. Others prefer to outsource or use existing technologies. Subsequently the company moved into a waiting niche for recommendation technology. By 2007, the company had partnered with The Wall Street Journal, solidifying their presence in the space.
Initially, Loomia's recommendation technology used a collaborative filtering
approach. However, as the company continued to innovate, content analysis was added sometime in 2006. At this point, the company was not necessarily using content analysis in conjunction with collaborative filtering.
In January 2008, Loomia added in a social context to improve the content recommendations. One of the products Loomia launched at this time was the SeenThis? application. It shows readers which articles and videos are popular within their specific social networks, predominantly through a Facebook app. Content comes from Loomia's clients (i.e.WSJ.com, CNET, and NBC.com), but the popularity amongst the social groups determines how widespread the content becomes.
By October 2008, Loomia blended all the inputs to find the best recommendations amidst all of the criteria, and this led to a soft launch of Targeted Content Discovery and Video Discovery products in January 2009.
technologies including Python
, MySQL
, Apache
, and CentOS
. The code base is mostly Python with portions in C
.
Loomia’s Targeted Content Discovery engine analyzes visitor behavior, textual and metadata, and social data to create recommendations that appear in an onsite module. As new content items are added, they are included in the system's calculations. For example, on The Wall Street Journal
, the module suggests other WSJ content based on what the user has read previously on the site and compared to what other users have read.
Loomia's Targeted Content Promotion feature within the recommendation engine is designed to help online publishers optimize their Web sites so that they can make more money off of their content. Loomia had experimented with TCP mapping to find out what sections of Web sites are the best revenue drivers, and the company created this targeting feature in November 2008. It would be packaged into the Video Discovery and Targeted Content Discovery products that Loomia launched in early 2009
San Francisco, California
San Francisco , officially the City and County of San Francisco, is the financial, cultural, and transportation center of the San Francisco Bay Area, a region of 7.15 million people which includes San Jose and Oakland...
in the United States. Loomia offers a module that recommends content on a Web site. The company is part of a growing Internet
Internet
The Internet is a global system of interconnected computer networks that use the standard Internet protocol suite to serve billions of users worldwide...
trend that aims to bridge the gap between technological capabilities and user intents. Loomia's technology analyzes the content on the Web site, as well as user behaviors and social contexts to offer additional content that reflects the user's interests. The technology is reported to find the overlap between these diverse datasets as well as matching it against publisher content preferences. In doing so, Loomia's technology attempts to surface publishers' most valuable content and recommend articles and videos that matter to users.
Loomia has worked with major media companies to optimize their Web site content such as Time.com, The Wall Street Journal
The Wall Street Journal
The Wall Street Journal is an American English-language international daily newspaper. It is published in New York City by Dow Jones & Company, a division of News Corporation, along with the Asian and European editions of the Journal....
, Forbes
Forbes
Forbes is an American publishing and media company. Its flagship publication, the Forbes magazine, is published biweekly. Its primary competitors in the national business magazine category are Fortune, which is also published biweekly, and Business Week...
, CNET
CNET
CNET is a tech media website that publishes news articles, blogs, and podcasts on technology and consumer electronics. Originally founded in 1994 by Halsey Minor and Shelby Bonnie, it was the flagship brand of CNET Networks and became a brand of CBS Interactive through CNET Networks' acquisition...
, US News & World Report, and others. The content recommendation module can be found on these sites under the header of "People Who Read This Also Read."
Loomia was founded by David Marks, Ken Fromm, and Francis Kelly in 2005.
The company is located in San Francisco, CA.
Chronology
- 2005 – Loomia is founded in San Francisco, CA
- June 2005 – Loomia launches its videocasting and podcastPodcastA podcast is a series of digital media files that are released episodically and often downloaded through web syndication...
ing technology. - January 2006 – Loomia launches its content recommendation technology.
- September 2006 – Loomia launches on Audible.comAudible.comAudible.com is an Internet provider of spoken audio entertainment, information, and educational programming.Audible sells digital audiobooks, radio and TV programs, and audio versions of magazines and newspapers....
recommending paid content. - March 2007 – Loomia acknowledged in Cool Vendors in Media, 2007 by GartnerGartnerGartner, Inc. is an information technology research and advisory firm headquartered in Stamford, Connecticut, United States. It was known as GartnerGroup until 2001....
. - July 2007 – Loomia partners with The Wall Street JournalThe Wall Street JournalThe Wall Street Journal is an American English-language international daily newspaper. It is published in New York City by Dow Jones & Company, a division of News Corporation, along with the Asian and European editions of the Journal....
. - January 2008 – Loomia launches SeenThis? FacebookFacebookFacebook is a social networking service and website launched in February 2004, operated and privately owned by Facebook, Inc. , Facebook has more than 800 million active users. Users must register before using the site, after which they may create a personal profile, add other users as...
application. - April 2008 – Loomia raises $5 million in Series A funding from Asset Management Company, Teléfonica Capital, and Peacock Equity.
- January 2009 – Loomia soft launches Targeted Content Discovery and Video Discovery products.
- January 2009 – Loomia is a 2009 OnMedia 100 winner.
History
Founded in 2005, Loomia garnered funding from a number of angel investors in Silicon Valley. Loomia launched its product in June of that year. Originally, the company offered podcasting recommendations on loomia.com. People could subscribe to podcasts, listen to them onsite, or download them. The recommendation engine that was part of the Web site gave users recommended podcasts based on the individual's ratings and the ratings of other community members.However, Loomia soon saw other opportunities for their recommendation engine, and Loomia began using their technology to suggest new Web pages to users on content and ecommerce sites While big sites like Amazon have the capital to develop their own recommendation technology, many other publishers don't have the budget for such development. Others prefer to outsource or use existing technologies. Subsequently the company moved into a waiting niche for recommendation technology. By 2007, the company had partnered with The Wall Street Journal, solidifying their presence in the space.
Initially, Loomia's recommendation technology used a collaborative filtering
Collaborative filtering
Collaborative filtering is the process of filtering for information or patterns using techniques involving collaboration among multiple agents, viewpoints, data sources, etc. Applications of collaborative filtering typically involve very large data sets...
approach. However, as the company continued to innovate, content analysis was added sometime in 2006. At this point, the company was not necessarily using content analysis in conjunction with collaborative filtering.
In January 2008, Loomia added in a social context to improve the content recommendations. One of the products Loomia launched at this time was the SeenThis? application. It shows readers which articles and videos are popular within their specific social networks, predominantly through a Facebook app. Content comes from Loomia's clients (i.e.WSJ.com, CNET, and NBC.com), but the popularity amongst the social groups determines how widespread the content becomes.
By October 2008, Loomia blended all the inputs to find the best recommendations amidst all of the criteria, and this led to a soft launch of Targeted Content Discovery and Video Discovery products in January 2009.
Technology
Loomia's content recommendation technology is built upon multiple Open SourceOpen source
The term open source describes practices in production and development that promote access to the end product's source materials. Some consider open source a philosophy, others consider it a pragmatic methodology...
technologies including Python
Python (programming language)
Python is a general-purpose, high-level programming language whose design philosophy emphasizes code readability. Python claims to "[combine] remarkable power with very clear syntax", and its standard library is large and comprehensive...
, MySQL
MySQL
MySQL officially, but also commonly "My Sequel") is a relational database management system that runs as a server providing multi-user access to a number of databases. It is named after developer Michael Widenius' daughter, My...
, Apache
Apache HTTP Server
The Apache HTTP Server, commonly referred to as Apache , is web server software notable for playing a key role in the initial growth of the World Wide Web. In 2009 it became the first web server software to surpass the 100 million website milestone...
, and CentOS
CentOS
CentOS is a free operating system based on Red Hat Enterprise Linux . It exists to provide a free enterprise class computing platform and strives to maintain 100% binary compatibility with its upstream distribution...
. The code base is mostly Python with portions in C
C (programming language)
C is a general-purpose computer programming language developed between 1969 and 1973 by Dennis Ritchie at the Bell Telephone Laboratories for use with the Unix operating system....
.
Loomia’s Targeted Content Discovery engine analyzes visitor behavior, textual and metadata, and social data to create recommendations that appear in an onsite module. As new content items are added, they are included in the system's calculations. For example, on The Wall Street Journal
The Wall Street Journal
The Wall Street Journal is an American English-language international daily newspaper. It is published in New York City by Dow Jones & Company, a division of News Corporation, along with the Asian and European editions of the Journal....
, the module suggests other WSJ content based on what the user has read previously on the site and compared to what other users have read.
Loomia's Targeted Content Promotion feature within the recommendation engine is designed to help online publishers optimize their Web sites so that they can make more money off of their content. Loomia had experimented with TCP mapping to find out what sections of Web sites are the best revenue drivers, and the company created this targeting feature in November 2008. It would be packaged into the Video Discovery and Targeted Content Discovery products that Loomia launched in early 2009
Competitors
A number of other technology companies are working to carve out a niche in the recommendation technology space. One such competitor is Aggregate Knowledge, which has raised a total of $25 million in venture capital to date.See also
- Information filtering systemInformation filtering systemAn Information filtering system is a system that removes redundant or unwanted information from an information stream using automated or computerized methods prior to presentation to a human user. Its main goal is the management of the information overload and increment of the semantic...
- Collaborative filteringCollaborative filteringCollaborative filtering is the process of filtering for information or patterns using techniques involving collaboration among multiple agents, viewpoints, data sources, etc. Applications of collaborative filtering typically involve very large data sets...
- Content analysisContent analysisContent analysis or textual analysis is a methodology in the social sciences for studying the content of communication. Earl Babbie defines it as "the study of recorded human communications, such as books, websites, paintings and laws."According to Dr...
- Recommendation systemRecommendation systemRecommender systems, recommendation systems, recommendation engines, recommendation frameworks, recommendation platforms or simply recommender form or work from a specific type of information filtering system technique that attempts to recommend information items Recommender systems, recommendation...