The number of online services providing users with real-time recommendations has increased exponentially over the last few years. Recommender Systems that were originally only accessible to a limited number of high-tech companies are now widely available through a growing number of both technical choices and vendors. The acceptance, however, of automatically delivered recommendations by users depends on numerous factors that go far beyond the algorithms that constitute the major focus of researchers.

Over the past 10 years, Strands has been creating and operating recommender systems in a multitude of domains, ranging from digital music to fitness plans and personal finance management, and in a multitude of business settings ranging from lightweight integrations to highly-coupled integrations within secure bank environments.

As summarized by Neal Lathia of MobBlog, below are the top 10 lessons we’ve learned developing, deploying, and operating real-world recommender systems:

• Lesson 1. Make sure a recommender is really needed! Do you have lots of recommendable items? Many diverse customers?… also think Return-on-Invesment… a more sophisticated recommender may not deliver a better ROI.
• Lesson 2. Make sure the recommendations make strategic sense. Is the best recommendation for the customer also the best for the business? What is the difference between a good and useful recommendation? Good recommendations vs useful recs; obvious recommendations may not be useful; risky recs may deliver better long-term value.
• Lesson 3. Choose the right partner! Select the right rec vendor vs hire some #recsys09 students. If you are a big company the best thing you can do is organize a contest.
• Lesson 4. Forget about cold-start problems (!) …. just be creative. The internet has all the data that you need (somewhere…).
• Lesson 5. Get the right balance between data and algorithms. 70% of the success of a recommendation system is in the data, the other 30% in the algorithm.
• Lesson 6. Finding correlated items is easy but deciding what, how, and when to present them to the user is hard… or don’t just recommend for the sake of it. Remember, user attention is a scarce and valuable resource. Use it wisely! … dont make a recommendations to a customer who is just about to pay for items at the checkout! User interface should get at least 50% of your attention.
• Lesson 7 Don’t waste time computing nearest neighbours (use social connections)… just mine the social graph. Might miss useful connections?
• Lesson 8 Don’t wait to scale!
• Lesson 9: Choose the right feedback mechanism. Stars vs thumbs …. the YouTube problem. More research on implicit and other feedback mechanisms is needed. The perfect rating system is no rating system! … focus on the interface.
• Lesson 10 Measure Everything! … business control and analytics is a big opportunity here.

Keynote Takeaway

Think about application context; Focus on interface as much as algs; be creative with startup data. … the UI needs to get the lion’s share of the effort (50%) compared to algorithms (5%), knowledge (20%), analytics (25%).

We are pleased to invite you to participate in this first workshop on Recommender-based Industrial Applications, to be held on Sunday, October 25th, 2009 in New York City, USA, in conjunction with The 3rd ACM Conference on Recommender Systems (New York City, October 22-25, 2009).

Complete workshop schedule and details can be found here.

Recommender systems help users deal with large amounts of information by assisting them in their decision-making processes.  Recommender systems have been applied very successfully in a variety of domains, and one of their most exciting characteristics is that they combine interest from industry while posing very interesting research challenges, having significant impact on end user experience, and on business.

Motivation and Topics

Recommender-based industrial applications have hit the mainstream: they are being used today by millions of users in a variety of domains (e.g., film, music, book purchases, travel, advertising, etc.), having significant impact on end users and contributing to the generation of millions of dollars of revenue in some industries.

In addition, the explosion of social network websites, on-line user-generated content platforms, and tremendous growth in computational power of mobile devices are generating incredibly large amounts of user data, and an increasing desire of users to find what best matches their personal interests.  This is creating new technical challenges as well as new business opportunities.  However, in spite of significant progress in the research community, there are still important gaps in making accurate and timely recommendations in industrial applications.

This workshop aims at bringing the gap between academic researchers and industry practitioners on the area of Recommender Systems.  We are interested both in research work that faces real industry problems, and in industry cases that create research challenges.

We aim to discuss problems the industry is facing in real-world applications when applying recommendation and personalization techniques.  The goal is to bring together top-level researchers from academia and recommendation practitioners.  Ideally the workshop should serve to establish new collaborations and projects involving academic researchers and companies.

Topics of interest include industrial applications and research challenges related but not limited to:

• case studies of recommender system implementations and deployments
• personalization vs. content-based vs. collaborative-based applications
• evaluation and user studies of recommender systems
• recommendations in the long tail
• user preferences and recommender systems
• social and cultural impact of recommender systems
• security and privacy in recommender systems
• sparsity and lack of data in recommender systems
• context-aware and ubiquitousness in recommender systems
• user interfaces and usability issues in recommender systems
• scalability in large recommender systems
• new business models related to recommendation and personalization
• search vs. recommendation

Workshop Chairs

• Dr. Alejandro Jaimes, Telefonica Research
• Dr. Marc Torrens, Strands

Please address questions to recsys [at] strands.com.

If you are in Europe and you are interested in recommendation technologies, Recked is for you.

Recked is an informal event for 100 engineers interested in recommender systems, organized by Wakoopa, the software and games discovery start-up, and Strands.

Held on January 26th in Amsterdam, The Netherlands, Recked will focus on how to implement collaborative filtering for your product in a manageable and practical way. Three experienced speakers will give you all the real-world use cases and solutions you’ll need to start building your own recommendation platform.

The speakers at the event will be Dominiek ter Heide, founder of Reccoon, the location based services start-up (and finalist in the Strands Call for Recommender Systems); Coen Stevens, Lead Recommendations Engineer at Wakoopa; and Jim Shur, Strands Chief Software Architect.

For more information and to sign up, please visit to the Recked website. Looking forward to seeing you there!

We believe the future of the web is about personalization. And if you are coming to Recked, you probably agree with us. Personalized TV stations, personalized news, personalized advertising, personalized shopping experiences…

Two examples of our technology in action can be found here:

SkyMall

Iheartmovies

Strands technology

Strands technology is based on a complementary set of statistical analysis, artificial intelligence, and complex filtering algorithms, collectively referred to as the Strands Social Recommender. Exploiting human-generated links between items, implicit and explicit user behavior, and analysis of certain intrinsic characteristics, these algorithms generate associations that result in a compelling representation of how society considers and uses the products, content, and information it creates and consumes. Learn more here.

Strands Widgets and APIs

Whether you use the Strands recommender widget or our APIs, Strands Social Recommender is added in three steps and is customized to be aligned with your marketing needs. You can track increases in sales, page views, average order value, CTR and more. Most important, Strands Social Recommender will help you better understand your customers.

Industry events

Strands has been actively involved in the recommendation industry since its foundation. In 2006, Strands organized the first industry event, Recommenders06, getting together the brightest minds in academia and industry to discuss the challenges and opportunities of recommendation technologies.

In 2007, Strands lead the Industry Program of the 1st ACM Conference on Recommender Systems. In 2008, Strands lead the Industry Program of the 2nd ACM Conference on Recommender Systems and organized the $100k Call for Recommender Start-ups. You might also be interested in the blog post “What is the recommender industry?” by our Chief Scientist Rick Hangartner. For us, it’s a pleasure to be involved in Recked this year.

Interested in Recommendation Technologies? Please visit our website, call our New York office (+1) 646 213 2000, our Madrid office (+34 91 770 1856) or email us.

You can also add Strands Recommender Widget to your site now.

See you in Amsterdam !!

In addition to the winner, the Jury selected two runners up: the location-based recommender developer Reccoon (2nd place), and Iletken (3rd place), a recommendation engine for rapidly emerging contents like news/rss feeds that utilizes social data.

Gravity R&D, Reccoon and Iletken participated in the Strands $100K Call for Recommender Start-Ups together with a total of 68 scientists and entrepreneurs from 24 teams in 15 countries who presented 26 projects. Five finalists were selected to present their projects today at the ACM Conference on Recommender Systems – RecSys08 in Lausanne. This is an impressive pool of talent and innovation, congratulations to all of them!

The Winner

Gravity R&D with its associate, Reignsoft, have created IMPRESS, a “magic button” that provides TV viewers with instant personalized entertainment at any given time with relevant program tips instantaneously on customer demand. It automatically schedules recordings with the highest probability based on user’s interest.

Gravity R&D is a four person team (Domonkos Tikk, István Pilászy, Gábor Takács and Bottyán Németh) from Budapest University of Technology in Hungary, and it was founded to exploit the experience learned at the Netflix Prize competition. It is specialized in algorithms, methods and practical application development for recommendation systems.

Reccoon helps people discover new places based on their input, current location and current time:

Iletken is a hybrid recommendation engine for services like news and RSS feeds:

The other two finalists were SentiMetrix and Commendo. See their presentations below:

SentiMetrix extracts and quantifies the huge and growing number of text-based opinions expressed through online media worldwide.

SentiMetrix @ Strands $100K Call for Recommender Start-Ups – RecSys08

The seven members of the Jury were:

As you know, Strands seeks to identify the best early-stage project in the area of recommendation technologies. Finalists are invited to present their projects during the ACM Conference on Recommender Systems (RecSys08) this October 23rd to 25th, 2008 in Lausanne, Switzerland. The Winner will be offered an investment of $100,000 from Strands, Inc.

A total of 68 scientists and entrepreneurs from 24 teams in 15 countries presented 26 projects. Countries included Australia, Austria, Canada, China, Finland, Germany, Greece, Hungary, Japan, Mexico, Romania, Spain, The Netherlands, Turkey and the USA. Areas where the recommendation technologies were applied are: pharmaceutical industry, cosmetics, video content, online media content, people and relations, TV content, search, events, social enterprise, advertising, location based services, travel and food.

And here is the list of the five finalists. Good luck to you all in Switzerland, this is very exiting for all of us!!

IMPRESS – Instant Entertainment, by Gravity R&D

IMPRESS “magic button” provides TV viewers instant personalized entertainment at any given time with relevant program tips instantaneously on customer demand. It automatically schedules recordings with the highest probability on user’s interest.

Gravity R&D was founded to exploit the experience learned at the Netflix Prize competition. It is specialized in algorithms, methods and practical application development for recommendation systems.

Team of 4: Domonkos Tikk, István Pilászy, Gábor Takács and Bottyán Németh. University: Budapest University of Technology. Hungary

SentiMetrix, Opinion-based Recommendations
SentiMetrix extracts and quantifies the huge and growing number of text-based opinions expressed through online media worldwide. SentiMetrix has automated sentiment extraction/analysis/scoring, the ability to find and quantify opinions in text.

SentiMetrix was founded in 2007 and it is based on the award-winning OASYS technology.

Team of 4: Patrick McBride, Vadim Kagan, V.S. Subrhamanian and Diego Reforgiato. University: University of Maryland Institute for Advanced Computer Sciences, USA

iletken, Personally Relevant Content Based On Social Connections

Iletken, which means “Conductive” in Turkish, is a hybrid recommendation engine for services like news and RSS feeds. The core system of “Iletken” mimics the dynamics behind real life information dissemination to enable friends to share and conduct relevant information.

In contrast to traditional social networks, it maintains weighted graphs of social proximity among users for different categories of interest. Analyzing user behavior, Iletken dynamically updates its social graphs and uses this data to determine information conductivity among peer.

Team of 4: Murat Deniz Oktar, Baris Can Daylik, Firat Gelbal and Selcuk Atli. Universities: Koc University Istanbul, RPI New York and TU/e, Eindhoven.

Reccoon, location-based recommender

Taking advantage of the vast amount of GPS-enabled mobile devices, Reccoon helps people discover new places based on their input, current location and current time. It also adjusts recommendations to attention profile (e.g. Last.fm listening history). Reccoon responds to the simple question: what are my options for tonight?

Team of 2: Peter Tegelaar and Dominiek ter Heide. The Netherlands

Commendo – Drug Design Recommendation

Commendo uses recommendation technologies to optimize the drug design process in the pharmaceutical industry, including speeding up drug development and the minimization of adverse drug reactions.

Commendo was founded out of the project team “BigChaos”, which still participates very successfully in the Netflix Prize competition.

Team of 4: Andreas Töscher, Michael Jahrer, Georg Preßler and Michael Schrotter. Universities: Technical University Graz and University of Applied Sciences Mittweida, Austria

Back in March we announced the “Strands $100,000 Call for Recommender Start-Ups“, the Fastest Path to Fund your Project. Now that we are getting closer to the end of the submission period, next September 15th, we’d love to receive your proposal!

As you know, the Call is open to individuals or sole proprietors and privately held businesses throughout the world, and five Finalists will be invited to present their projects during the ACM Conference on Recommender Systems (RecSys08) next October 23rd to 25th, 2008 in Lausanne, Switzerland. The Winner will receive a commemorative plaque and an offer of a $100,000 investment in the form of a convertible loan.

For further information, please visit http://recommender-startups.strands.com or contact the Strands $100,000 Call for Recommender Start-ups organizers at recommender-startups@strands.com.

Important dates:
September 15th: Proposal submission period ends
October 6th: Five Finalists are announced
October 23rd-25th: Presentations of Finalists at RecSys08
October 25th: Winner Announced

Contact and updates:
Email proposal to: recommender-startups@strands.com
http://recommender-startups.strands.com
http://blog.Strands.com
http://recsys.acm.org

MyStrands is announcing today the “Strands $100,000 Call for Recommender Start-ups“.

We seek to identify the best early-stage project in the area of recommendation technologies, considering the technology, business opportunity and team behind the project (without limitations as to which field the technology is applied).

The Winner will be offered an investment of $100,000 from Strands, Inc. the parent company of MyStrands.

Candidates should submit a one-slide presentation in quad-chart format (example, more examples) by September 15th, 2008 to recommender-startups@strands.com, together with the team bios (in addition to this, an optional 2-minute video uploaded to YouTube describing the start-up enterprise would be highly appreciated).

Eligibility: The Call is open to individuals or sole proprietors and privately held businesses throughout the world.

Five Finalists will be invited to present their projects during the ACM Conference on Recommender Systems (RecSys08) next October 23rd to 25th, 2008 in Lausanne, Switzerland. Finalists will be announced on October 6th. All Proposals will be judged using the following judging criteria: (a) implementation and integration of recommendation technologies, (b) originality and creativity, (c) likelihood of long-term success and scalability, (d) effectiveness in addressing a need in the marketplace, and (e) team bios.

Five grants. Each Finalist will obtain a $1,500 travel grant to attend RecSys08; Strands, Inc. will also cover the registration fees for the Conference, for one person per Finalist.

The final selection process will include on-site presentations of each project during RecSys08. Finalists will make three presentations of 5 minutes each (focused on technology, business and the team respectively) in front of the Jury and the attendees of the Conference.

The Jury will be composed of renowned experts in the academic, industry and venture capital communities.

The Winner will be announced on October 25th, 2008 during the Gala Dinner at RecSys08. The Winner will receive a commemorative plaque and an offer of a $100,000 investment in the form of a convertible loan.

Proposal submission period begins on March 12th and ends on September 15th, 2008.

Further information: Please visit http://recommender-startups.strands.com or contact the Strands $100,000 Call for Recommender Start-ups organizers at recommender-startups@strands.com.

Important dates:
March 12th: Proposal submission period begins
September 15th: Proposal submission period ends
October 6th: Five Finalists are announced
October 23rd-25th: Presentations of Finalists at RecSys08
October 25th: Winner Announced

Contact and updates:
Email proposal to: recommender-startups@strands.com
http://recommender-startups.strands.com
http://blog.MyStrands.com
http://recsys.acm.org

This conference builds on the success of Recommenders06 Summer School organized by MyStrands in Bilbao in 2006, and the 1st International Conference in Minneapolis last year. In these events many members of the practitioner and research communities valued the rich exchange of ideas made possible by the shared plenary sessions.

Why should this matter to you? As our Chief Scientist Rick Hangartner recently wrote:

Search engines as we know them will never disappear. In the near term, search engines will increasingly incorporate simple recommender technologies to handle approximate queries … But in the long term, the recommender industry will be larger, and recommender technologies will be more pervasive than the search industry and search technology as we know it.

If this were not enough, this year’s event will take place in beautiful Lausanne, Switzerland.

ACM Recommender Systems 2008 is chaired by Pearl Pu, General Chair, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Please visit the RecSys08 website for further information regarding topics of interest, important dates and more.

There were too many ideas and themes that interested me this year, but in particular, I was very interested to hear Khrishna Bharat, principle scientist at Google, give the keynote. Greg Linden from Findory gives a good overview, which I won’t repeat. Dr. Bharat’s talk was a very detailed argument of journalism as a necessary cultural function, and not just a reflection (or exaggeration) of online novelty and whim.

His main argument was of journalism and free press being a necessary agent (and product of) democracy. While Google News has come under fire for potentially undermining the economic viability of online journalism, Krishna argues that Google News actually increases traffic to such sites.

However, much of his emphasis (and closing remarks), came in his discussion of the journalists who risk their lives to cover developments in hostile international countries and situations. Many people may have better tools and options for the exploration and discovery of relevant news items, especially in the realm of technical or entertainment journalism. However, the biggest threat to journalism as an agent of democracy may be the increasing number of reporters killed pursuing their trade.

Any sort of news is a function of three populations: Those who collect and distill the event into words, those who editorialize and sort these events into meaningful chunks of information, and finally those of us who consume this information. All of the technology in the world cannot replace a single journalist, and Bharat believes that this is actually one of the most important issues for journalism in general, both online or print.

Justin Donaldson, Researcher, MyStrands

Yesterday featured a very interesting keynote speech from Khrishna Bharat, Principal Scientist from Google, about the history and future of news journalism and the social responsibility we all share in ensuring the continued freedom of speech. He also touched on the process by which Google crawls, clusters, ranks, classifies the most relevant stories in Google News. Followed by some insight into the increased user engagement they were able to realize with the introduction of their personalized news stories. The clickthrough of personalized news stories is indeed higher than on just a blind list of “top stories”.

The keynote was followed by a number of academic papers presentations – focused on the hot topics of privacy and trust in collaborative filtering engines. Indeed some very interesting research going on in these fields, and I look forward to seeing what the continued research here bears out in the coming months and years.

After lunch, I was honored to take part in a panel with the focus of “Where should we be investing most in research and practice to increase the value of recommenders?”. This was the opportunity for the industry folks like ourselves to provide some insight to the academics about the “real world” issues that we are trying to solve or improve. It was a lively discussion that extended the dialog on recommenders beyond the science and into user experience, consumer value and business models built around them. The panel included:

• Joaquin Delgado, CTO, Lending Club Corp.
• Jason Herskowitz, VP of Consumer Products, MyStrands
• Kartik Hosanagar, Assistant Professor, Wharton School of Business, University of Pennsylvania
• David Jennings, DJ Alchemi LLC
• Zac Johnson, Product Manager, All Media Guide, Inc.

The day closed out with Poster Sessions by the academic community and some very interesting demos, with the lively discussion moving on to dinner and drinks. Today’s session promises to bring more great discussion. Look for another post later….

On Monday the 15th Atakan Cetinsoy participates in Mobile 2.0 in San Francisco, in the panel Disruptive or New Business Models. The Mobile 2.0 conference brings together experts and thought leaders from all aspects of the mobile ecosystem, including investors, mobile carriers, device manufacturers, mobile application developers, and web technologists.

That same day, while Noyda Matos and Albert De Reina attend the Widget Summitt, Scott Kveton will be at the API Conference.

On the other side of the Atlantic, our mobile guru Oliver Bremer will be at the Symbian Smartphone Show in London, giving a keynote on Building content-focused social networks to attract and retain subscribers.

And finally, on October 19th and 20th, part of the team (Francisco, Jim, Jason and Justin) will attend the ACM Recommender Systems 2007 Conference in Minneapolis, Minnesota, USA. This conference brings together research and practice to explore the latest innovations, discuss important challenges, and advance our understanding of recommender systems.

We are specially proud of this event, that builds on last year’s Recommenders06 organized by MyStrands. Francisco is chairing the Industry Committee and Jason will participate in the panel Where should we be investing most in research and practice to increase value of recommenders?

We hope to see you at these events, let us know if you are attending any of them.

Friday October 19th: Where should we be investing most in research and practice to increase value of recommenders?

• Moderator: Todd Beaupre, Yahoo, Inc.
• Joaquin Delgado, CTO, Lending Club Corp.
• Jason Herskowitz, VP of Consumer Products, MyStrands
• Kartik Hosanagar, Assistant Professor, Wharton School of Business, University of Pennsylvania
• David Jennings, DJ Alchemi LLC
• Zac Johnson, Product Manager, All Media Guide, Inc.

Saturday October 20th: Appraisal of Recommender Systems

• Moderator: Kaushal Kurapati, Ask.com
• Delip Andra, CEO, Minekey, Inc.
• Jennifer Consalvo, Director of Personalization, AOL
• Greg Linden, CEO, Findory, Inc.
• Shail Patel, Platform Leader, Unilever Corporate Research
• Neel Sundaresan, Director, eBay Research Labs
• Tim Vogel, Chief Scientist, Aggregate Knowledge, Inc

As previously announced, Krishna Bharat, Principal Scientist at Google, will serve as Keynote Speaker for the Conference. For additional content and information, please visit the Conference Program. For last year’s Recommenders06 panels and speakers, please visit Recommenders06.com.

* A Keynote address by Krishna Bharat, principal scientist at Google and creator of Google News.

* 16 full-length technical papers, plus an exciting poster and demo program

* Still to be finalized — two industry-driven panel sessions on topics of current importance in the field.

Don’t miss the conference. RecSys 2007 will be held in Minneapolis, Minnesota October 19-20, 2007. Registration and hotel bookings are now open at the conference website http://recsys.acm.org. See you there!

Please visit the RecSys07 website for further information.

We are very pleased to announce ACM Recommender Systems 2007.

This Conference builds on a wonderful legacy of research workshops and the Recommenders06 Summer School on the Present and Future of Recommender Systems, organized by MyStrands last year in Bilbao.

The Conference will bring together the leaders of this field–from both research and practice–to explore the latest innovations, discuss important challenges, and advance our understanding of recommender systems.

RecSys07 is organized by Prof. Joseph A. Konstan (General Chair). Prof. John Riedl and Prof. Barry Smyth are the Research Program co-Chairs. As of today, the Practice/Industry Program Committee is compossed of:

• Dr. Francisco J Martin, MyStrands (Practice/Industry Program Chair);
• Todd Beaupre, Yahoo! Inc;
• Rafael Camargo, Motorola, Inc;
• Maikki Frisk, Nokia Corporation;
• Jason Herskowitz, AOL Inc;
• Kaushal Kurapati, Ask.com;
• Dominic Pride, France Telecom, SA.

Please visit the RecSys07 website for further information.