Using algorithms to give personalized recommendations is hard. A lot of online services try to leverage their users' social graphs to determine the stories, books, songs or movies that are potentially of interest to them. Given that your own interests can be quite different from those of your friends, though, these systems are often limited. my6sense, on the other hand builds a personalized and constantly evolving profile for all of its users and provides recommendations purely based on what its algorithm thinks is most likely to be interesting to you. Starting today, Android users will be able to find the most interesting items in their RSS, Twitter, Facebook and Google Buzz feeds with the help of My6Sense.
Just the other day, I introduced my mother to music recommendation service Pandora. We'd been discussing how my grandfather used to love listening to barbershop music and she said she missed it and would love to find a way to listen. Finding the music she wanted, however, was not so easy, as we needed to find the right band or song that exemplified the music she wanted to hear - it was a journey through Google, Wikipedia, AllMusic and a number of other sites.
Today, Pandora will make this type of musical browsing easier with the addition of station-creation based on musical genres, instead of just bands or songs. Update: Pandora says it announced a day early and that genre stations will actually be live on Wednesday.
Appolicious, the website known for its mobile application recommendations, has today launched a revamped Android-focused offering at AndroidApps.com, complete with an accompanying mobile application.
The Yahoo partner, which originally debuted back in fall of 2009, has consistently offered a useful service that digitizes "word of mouth" recommendations, allowing you to connect with friends who share your interests in order to find new apps. Now that process is even easier, thanks to the new website, its improved search engine an the new Android app.
A few weeks ago I wrote that we've moved to an era of the Web that is beyond social. My contention is that successful services of this era of the Web will be ones that filter, structure and personalize the vast amount of data coming onto the Web. An example of this kind of application is Hunch, which this week re-launched as an Internet personalization service. Hunch is one of a number of modern web services aiming to connect you not only to other people, but to products and objects.
Hunch co-founder and Chief Product Office Caterina Fake told Wired in a recent profile that "the ultimate goal of the company is to map every person on the Internet to every object on the Internet, be that a product, a service, or a person."
fbLike, the OpenGraph-powered Facebook dashboard, has introduced a new kind of Facebook advertising system.
Centered on fbLike's product comparison engine, myBrands, the system leverages Facebook's "Like" recommendation function to create an unobtrusive advertising network. Instead of charging based on the standard CPM (a fee per thousand views), fbLike instead charges based on CPL, or "cost per Like."
Facebook just announced the availability of a new feature for users creating accounts on the social network: Suggested Interests. Facebook will now recommend that new users sign up for updates from ("Like") publishers with high reader engagement and subscribed-to by people demographically similar to themselves. That's a unique combination of factors that only Facebook could offer.
If this intersection of 3 key social software trends is someday exposed more fully to all 500 million Facebook users and more - the Facebook vs. Google battle could become a fight between Recommendation and Search. Facebook recommendations are in the sidebar for most users today, but they are so powerful that it's worth betting they'll be center stage in the future.
Cross reference a person's Twitter friendships with their Foursquare favorites with their Hunch.com articulated "taste graph" and what do you get? Interesting personalized restaurant recommendations, for one thing.
Taste-gathering startup Hunch is experimenting with a recommendation service that cross references social graph connections on other services with the large set of unusual questions its users have answered. Questions like "do you like facial hair on men? Yes? Well, 48% of our users have said that." The end result is a simple prototype website where you enter a city and your Twitter username and Hunch will show you Foursquare venues it thinks you'll like. Or at least it thinks that people on Hunch who are like your friends on Twitter tend to like those places, on Foursquare. Crazy? Maybe not.
Fanit is another start-up that has discovered the gospel of game play and is using it to promote their music recommendation experience.
Fans support their favorite artists and bands by purchasing badges. 100% of the money for the badges go to the artists, according to the company's PR representative. As the fan purchases badges and engages in recommendation actions, they earn "rank." That rank gives the fan a chance at "superfan" status and, according to the company, creates opportunities for interactions with the listener's favorite musicians.
From shopping to music, the overload of information on the Web has been shaped and ordered by recommendation engines. There are even tools like the browser extension GetGlue that purport to sail the entire recommendations ocean. But one very important aspect of the online experience has been overshadowed: video. Milan- and Tel Aviv-based Bee.tv, currently in beta, has introduced a proprietary, cross-platform recommendation service to personalize television, film and video viewing. Bee.tv aspires to do for video what Pandora or Last.fm do for audio.
"Bee.tv employs a proprietary algorithm that includes contextual and semantic analysis, collaborative filtering, and thematic push to deliver personalized TV, movie and video content recommendations."
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