MTV and partyStrands have teamed up to create an unforgettable interactive New Year’s 2007 experience in Time’s Square!

People in Times Square will be able to use their cell phones to send messages, vote to choose music videos and answer trivia questions on MTV’s 44 ½ giant HD screen in front of the MTV Studios.

People who aren’t able to make the New Year’s bash, can follow the party from home and even interact with the people in Time’s Square by logging onto www.mystrands.com/mtv.

Join us and bring in the New Year with partyStrands and MTV.

For those of you that just got a Nintendo Wii for the holidays (or like me you claim to have gotten for your kids but somehow you seem to be the one that is always playing it), I highly recommend that you download the Opera Browser (aka “Internet Channel”) for 500 Wii points and then fire up mystrands.tv on it. It works great and now easily brings personalized music into your living room.

Ho, ho, ho!

The MyStrands team

Those intrigued by the growing trend of visualization techniques, will be interested in the responses of Justin Donaldson to a questionnaire received from the British publication Five Eight magazine. Justin is a MyStrands’ researcher, Indiana University PhD Candidate, author of the Artist Network Visualization and the Maps of Recommendations, and 1st place Award Winner in Netsci06:

1. Explain briefly the outline of your service and what it hopes to achieve.
The Artistnet Interactive Visualization (see video) generates a network model from our user’s play activity. This is a very similar process to what we do “behind the scenes” with our recommender engine, although on a much, much smaller scale. However, even in this limited version you can often see how individuals relate to each other through their shared music tastes. The network visualization makes this apparent when two people’s “strands” of artists become connected. Most likely, those two people have something in common with their musical tastes, and may find something new and interesting in each other’s recent music listening history.

2. What do you think music visualization services bring to the table over other recommendation services?
Music visualization services represent recommendation information in a much higher level of detail. They expose recommendation as a “field of possibilities” instead of a simple ordinal list of results. Other MyStrands visualizations (such as recommendation mapping) seek to do just this. Exposing the relationships between the artists, songs, or albums in this fashion can help an individual come to a better understanding of how the artists, songs, and albums relate to one another in a broader cultural sense.

3. How are they of benefit to consumers and music users?
They benefit consumers and music users in the sense that they offer a richer portrait of the music possibilities available at any given time. People that are passionate about music are then able to explore their options in a more involved way.

4. How important are visuals to users experience of music in an age where cover art has been cast aside in the digital realm?
Cover art is not “completely” dead. It is experiencing a rebirth of sorts in the form of small thumbnail images (such as the “coverflow” visualization in iTunes). There is no doubt in my mind that the resolution and multimedia aspects of “album art” will continue to increase well beyond its current primitive state, and will once again become a significant component to a musical offering. With high definition televisions and sound systems at reasonable prices, the time is ripe for a multimedia “convergence” of sorts which will most likely kick off with music. In a sense, this is already happening with music videos. In fact, the most popular videos right now on youtube are often music videos, and MyStrands has just started providing recommendation for these videos with MyStrands.TV.

5. Where do you see these kind of services going in the future?
I think we as consumers will have a heightened awareness of our digital entertainment options. Eventually, recommendation service users will split into two camps: Those who want “push” recommendation, similar to conventional advertising where options are provided to them in a straightforward manner; and those who want “pull” recommendations, where an individual can explore the world of media possibilities relevant to them, and eventually play an active role in spreading new media that they enjoy. This sort of behavior already exists through informal social interaction (”Hey, did you hear about this new band?”…etc). However, recommendation systems will seek to automate and optimize it for everyone: listeners, artists, labels, studios, and venues. It’s gonna rock.

By Dr. Rick Hangartner, Chief Scientist, MyStrands. Guest column published in MSearchGroove

No, the headline on this entry is not a careless grammatical error. Nor is the question really “What is the recommender market?” That implies that “recommenders” are mature, well-defined technologies that deliver specific features and value to the online world. Emerging recommendation technologies are currently setting the standards for discovery and personalization in today’s social networking-dominated web 2.0 environment, and the future of online social networking is all about discovery and personalization. While search engines help you find things you know you are looking for, discovery helps you find the rest.

If we accept that every business must make its case in 10 to 20 seconds on its Web site, then we are all but forced to admit that recommenders, more than anything else, represent the conceptual answer to the question: “How can I get that visitor/user/customer to realize that I offer something of value to him or her?”

Although venture capitalists and Web 2.0 users may find that claim to be just the tiresome excuse they need for hitting the “Back” button, the point is that a good argument can be made that unlike search engines, the idea of recommenders is a formal concept that has as many different concrete examples as there are separate market applications. The recommender industry really is the business of pulling three components together into a system that helps a user-driven business convince their potential customers that they should stay for a while. These three elements include:

1) An effective model that relates the needs visitors have to what the business offers.

2) Quality data to build a model instance that relates specific needs to specific offerings.

3) Unobtrusive means for easily and quickly determining an individual user’s needs.

Note that these three components are not quite as simple as “good (statistical) algorithms,” “a lot of data,” or “simple user interfaces.” In the coming years, defining an effective model will increasingly involve a scientific approach to understanding user needs and the market strategy of the business. Gathering quality data will require more sophisticated understanding of which data is actually relevant to the model. Devising means for characterizing an individual user’s needs will depend on a refined understanding of how people implicitly and explicitly signal needs that they themselves may not even fully understand.

In short, the recommender industry is the evolving business of building and deploying systems that reify some of the psychology of human economic transactions. What this means for the marketplace seems relatively clear: 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 (e.g. “You asked for this, and based on similar queries/behavior by others, you might be looking for this.”). 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.

Beyond that, some general themes about the future of the recommender industry that seem to be worth watching for include:

Multiple revenue models: Unlike search engines, which primarily are monetized through contextual ads of some form, recommender systems will be monetized in multiple ways. Recommender technology suppliers will continue to partner with customer businesses to derive revenue as a share of explicit sales increases directly accredited to the recommender system. In the longer term, recommender technology will increasingly enable business models, including advertising schemes, which could not exist without it. An implicit valuation for a specific application of a recommender system will be derived from the enabled economic activity.

Increasing focus on how users require change over time: In that recommender systems reify aspects of the psychology of economic transactions, there is an increasing appreciation for the probable value of responding to how economic behavior changes over time. This includes how an individual’s needs change over time and how the needs of the community evolve. The former can, in part, be accommodated by simply taking care to build a recommender system instance using data that is an adequate sampling of individuals whose needs are changing. Adapting to the latter may also require recommender system models that explicitly incorporate features of how community needs to evolve.

New concepts of personalization: One of the recent trends in personalization is using information about an individual’s social network to better characterize that individual’s needs and interests. This may be just one aspect of a new concept of personalization that puts the focus not on delivering an isolating, customized experience to a person, but rather on connecting an individual with affinity communities who can provide information of value to that individual. Few people really want to be out there all alone. And for those explorers who do, they might, in reality, be hoping to build a community of like-minded souls or be waiting for others to catch up with them.

More than anything, the future of the recommender industry is a business that will continue to grow and become more sophisticated as the science of recommenders greatly develops and to increasingly encompasses computer science, psychology, economics and cognitive science.

Last week was an exciting one, with the announcement of BBVA investment in MyStrands. We want to thank you all for your support and enthusiasm! Here you’ll find some of the feedback received from the community:

New York Times, ReadWriteWeb, Digital Music News, Red Herring, Business Journal, Enrique Dans, Primate Blog

En Español aquí

We are very excited to announce that MyStrands has secured $24 million in its Series B2 round of funding. Spanish bank BBVA led the funding along with existing investor Debaeque. As you know, the last round of funding closed in June at $25 million, bringing the total capital raised to date to $55 million.

What is the value of MyStrands?

In the past four years, MyStrands has developed a scalable Personalized Discovery Platform and a Social Recommender Engine. The Social Recommender Engine provides real-time personalized recommendations of products and services through computers, mobile phones, and other Internet-connected devices; and takes into account that taste is context-sensitive and evolves over time.

These developments have already resulted in sales of $12 million during 2007.

Why more money?

The future of the Web is personalization and we are committed to leading it. These new funds will allow us to go one step further, enabling us to grow to the next level of product development, always respecting our core proposition: help people discover new things.

Why BBVA?

They endorse our vision and realize that summarizing and understanding people’s preferences will allow us to deliver relevant content to people, wherever they are.

What is BBVA?

BBVA is a financial services group with more than $782 billion in total assets, 42 million customers in 40 countries and a market capitalization of approximately $95 billion.

The BBVA Group maintains a leadership position in Spain, Mexico, and Latin America, and has started a growth and diversification strategy in Asia and the United States, where it recently bought Compass for approximately $9.6 billion.

We are Growing, Hiring!

This is the perfect moment to repeat it: we are hiring! We are bringing the best developers all over the world to come and join our team of 90 people. We are headquartered in Corvallis, Oregon, but you can join our teams in other cities. In the US: San Francisco, New York, Washington DC and Seattle (upcoming). International: Barcelona, Madrid, Valencia and Zaragoza in Spain; Helsinki in Finland or Sao Paulo in Brazil.