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Opera Solutions beats out hundreds of teams worldwide in contest to rank hotel search results with customers of the world’s largest travel agency. Jersey City, NJ, December 3, 2013 — Opera Solutions announces its recent top ranking in the Personalize Expedia Hotel Searches contest, hosted by Kaggle, Inc., beating out 337 other teams to claim the top slot. Expedia, the world’s largest online travel agency, asked competitors to develop a model that provides personalized hotel search results for each online travel shopper, awarding first prize to the model most accurate at recommending hotels the shoppers ultimately chose. Until now, Expedia has largely relied on users to screen and rank their own search results based on price, location, or other factors. Models that can sort and predict each user’s preferences thus provide a new way for Expedia to attract customers and make them more active and loyal. For this competition, the teams were given 2GB of shopping and purchase data as well as information on price competitiveness. They were tasked with applying analytics models to the data to sort the hotels and order them according to what they thought would generate the most clicks or purchases by each user. Scientists had to factor more than 50 attributes, including hotel characteristics, distance from target location, each user’s aggregate purchase history, and competitive travel agency information, into their models. Expedia used the Normalized Discounted Cumulative Gain error measure instead of the more common AUC error measure to judge the results. This is because this particular contest judged the ability to rank instead of simply the ability to filter, making the task especially difficult. Opera Solutions’ team, commendo, combined a number of advanced machine learning approaches using a technique called “Ensemble.” Ensemble uses multiple pattern-based models, with each model comparing two or three specific attributes and weighing the results for each user. “We are so proud of our commendo team for their hard work and dedication to this competition,” said Opera Solutions Chief Scientist and Global Head of R&D Jacob Spoelstra. “Competitions such as this one not only provide an opportunity to showcase the extraordinary talent we have here at Opera Solutions Places First in Expedia Big Data Challenge Profit from Big Data flow

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Page 1: Profit from Big Data flow Opera Solutions Places First in ... · PDF filein the Personalize Expedia Hotel Searches contest, hosted by Kaggle, Inc., beating out 337 other ... Opera

Opera Solutions beats out hundreds of teams worldwide in contest to rank hotel search results with customers of the world’s largest travel agency.

Jersey City, NJ, December 3, 2013 — Opera Solutions announces its recent top ranking in the Personalize Expedia Hotel Searches contest, hosted by Kaggle, Inc., beating out 337 other teams to claim the top slot.

Expedia, the world’s largest online travel agency, asked competitors to develop a model that provides personalized hotel search results for each online travel shopper, awarding first prize to the model most accurate at recommending hotels the shoppers ultimately chose. Until now, Expedia has largely relied on users to screen and rank their own search results based on price, location, or other factors. Models that can sort and predict each user’s preferences thus provide a new way for Expedia to attract customers and make them more active and loyal.

For this competition, the teams were given 2GB of shopping and purchase data as well as information on price competitiveness. They were tasked with applying analytics models to the data to sort the hotels and order them according to what they thought would generate the most clicks or purchases by each user. Scientists had to factor more than 50 attributes, including hotel characteristics, distance from target location, each user’s aggregate purchase history, and competitive travel agency information, into their models. Expedia used the Normalized Discounted Cumulative Gain error measure instead of the more common AUC error measure to judge the results. This is because this particular contest judged the ability to rank instead of simply the ability to filter, making the task especially difficult.

Opera Solutions’ team, commendo, combined a number of advanced machine learning approaches using a technique called “Ensemble.” Ensemble uses multiple pattern-based models, with each model comparing two or three specific attributes and weighing the results for each user.

“We are so proud of our commendo team for their hard work and dedication to this competition,” said Opera Solutions Chief Scientist and Global Head of R&D Jacob Spoelstra. “Competitions such as this one not only provide an opportunity to showcase the extraordinary talent we have here at

Opera Solutions Places First in Expedia Big Data Challenge

Profit from Big Data flow

Page 2: Profit from Big Data flow Opera Solutions Places First in ... · PDF filein the Personalize Expedia Hotel Searches contest, hosted by Kaggle, Inc., beating out 337 other ... Opera

Opera Solutions but also the power and potential of Big Data, predictive analytics, and machine learning techniques.”

commendo team member Michael Jahrer added, “We are honored to take first place in this contest. It was a tough challenge with many well-known, top-notch competitors.” Jahrer and his teammate, Andreas Toescher, have both competed in — and won — the Netflix Progress Prize (2008 and 2009) and the KDD Cup (2nd and 3rd places in 2010, 2011 (track 1), 2011 (track 2), and 2012 (track 2)). When asked how this competition stacked up to others, Toescher answered, “Popular Kaggle competitions are always tough. This one had over 300 of the world’s best data scientists.”

In 2008, the two scientists, along with Georg Pressler and Michael Schrotter, cofounded commendo, a product recommendation software company. Opera Solutions purchased the company in 2012.

Kaggle, the world’s largest community of data scientists, hosts dozens of contests each year working in conjunction with various companies that ask the winners to consult on real-world business projects. Fortune 500 companies, as well as smaller companies, offer these competitions to find new ways to solve the hardest data science problems.

Media Contacts:

Opera Solutions:Laura Tellere: [email protected] o: (646) 520-4338m: (917) 251-5467

#OpenCommunications, PR:Jonathan D. Lovitzo: (646) 383-3583 x110e: [email protected]

About Opera Solutions, LLCOpera Solutions (http://www.operasolutions.com, @OperaSolutions) combines advanced science, technology, and domain knowledge to extract predictive intelligence from Big Data and turn it into insights and recommended actions that help people make smarter decisions, work more productively, serve their customers better, grow revenues, and reduce expenses. Its hosted solutions, delivered as a service, are today delivering results in some of the world’s most respected organizations in financial services, healthcare, hospitality, telecommunications, and government. Opera Solutions is headquartered in Jersey City, NJ, with other offices in North America, Europe, and Asia. For more information, visit the website or call 1-855-OPERA-22.

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