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Scouta - Word-of-mouth media recommendations Web 2.0 style

Added on by Chris Saad.
Ever wondered what it would be like if you could get Amazon style recommendations about all forms of media across the net (yes even podcasts)?

Richard Giles a fellow Australian Web 2.0 junkie has created just such a thing. It's called Scouta and it just went live today.

From the home page:

There's nothing more powerful than a word-of-mouth recommendation. That's why Scouta uses recommendations from you and like-minded people to help find a needle in a haystack or a video in YouTube.

Find out more in our about page.
Get on and feed your media addiction (and then join me in the 12 step program).

Well done Richard!

A touching tale of Recommendation

Added on by Chris Saad.
This is a sweet story of love between a woman and her Amazon Recommendation Engine on The Onion.


"Pamela Meyers was delighted to receive yet another thoughtful CD recommendation from Amazon.com Friday, confirming that the online retail giant has a more thorough, individualized, and nuanced understanding of Meyers' taste than the man who occasionally claims to love her, husband Dean Meyers.

While the powerful algorithms that power Amazon's recommendations generator do not have the advantage of being able to observe Meyers' body language, verbal intonation, or current personal possessions, they have nonetheless proven more effective than Dean, who bases his gift-giving choices primarily on what is needed around the house, what he would like to own, and, most notably, what objects are nearby.

I don't know how Amazon picked up on my growing interest in world music so quickly, but I absolutely love this traditional Celtic CD," Meyers said. "I like it so much more than that Keith Urban thing Dean got me. I'm really not sure what made him think I like country music

It was nice to know that on my birthday, someone or something was out there thinking about me, and what boxed sets I wanted,"
This is a sweet story (in a strange, Amazon loves me more than my husband sorta way). Now imagine this sort of power across your entire Attention Profile.

Remember though... Touchstone is NOT a Recommendation Engine.

Via The Long Tail.

The PageRank of Personal Relevancy

Added on by Chris Saad.
Ilya recently posted some great data and analysis on the current state of RSS reading habits.

He goes on to explain many of the issues I alluded to in a previous post titled "Show me the money (or the pain)".

I think the question of information overload is answered. Yes there is an overload. But RSS is not the problem. In fact blogs and user generated news are not the problem either. They are just one source of information in our lives.

There are application events, presence changes from our friends, internal memos from head office, applications on our desktop and more all clamoring for our time...

So tools that try to cluster and suggest content from blogs and mainstream news sites are only (very) useful for part of the time.

Ilya goes on to make a great suggestion in his post. He recognizes that collaborative filtering has limitations, Keyword filtering is 'so 5 years ago' and that any one 'community voting' measurement will fall short.

With Touchstone we have gone to great lengths to cover all these usage scenarios. We have built a platform that accepts 'items' not 'RSS'. This means that we can source content from places other than RSS and then cache, rank and route them in a unified way.

Our 'rank' is not based on collaborative filtering or keyword filtering or community voting or previous reading behavior. It is based on some and none of these things at the same time. As such, our technology can work in a vacuum on a personal item behind the firewall, just as it can work on a news item that the whole world can see and link (read:vote) to.

Also, there is no 'handshake' period where our application tries to track your reading behavior over time. We are on the client side which means we have access to your browser history/cache, documents and email for an instant, broad and ongoing base of 'Attention Data' in order to determine your interests.

Ilya rightly compares this to PageRank. While PageRank uses incoming links as a vote to measure authority, it relies on a broader set of factors to make a decision and produce a number.

And because the result is a number rather than a binary 'yes or no' filter or an opaque recommendation, Touchstone can make intelligent presentation decisions when displaying the alert/content/information. The bigger the number the bigger the item on the page.

My friend Adam also posted about the 'Feed Overload Problem' on his blog.