amazon bjørn olstad concept composition concept design daniel tunkelang decision-making design patterns diligent search don tapscott efficiency enterprise search exploratory search faceted search facets FAST FF09 freebase google information retrieval ingenious search interaction design microsoft NLP paradox of choice personalization powerset recommendations recommenders relevancy satisficing searchme searchnuggets semantic seo sharepoint slideshare social topic pages traffic twitter usability user experience visualization wolfram alpha yggdrasil08
Vegard Sandvold
When Recommendations Become a Problem
Some choice good – excessive choice bad. That is the (condensed) Paradox of Choice, according to Barry Schwartz. We need some choice in order to exercise our free will, but the abundance of options we’re facing today (when shopping for groceries, entertainment, education and more) is actually quite overwhelming and paralyzing. No matter how... Read More »
Four Approaches to Music Recommendations: Pandora, Mufin, Lala, and eMusic
ReadWriteWeb gives us some nice examples of the kinds of recommendation systems I wrote about in my previous post. Pandora is content-based, although the features are extracted by humans. The result is high-quality data, but poor scalability. Mufin is a classical example of content-based music recommenders, using a purely algorithmic approach. Lala seems to be old-fashioned word-of-mouth recommendations put on the Internet. eMusic is a hybrid system, but combines social with expert, and social with content-based like Oscar Celma proposes. Apple Genius is most likely a typical collaborative filtering recommender, based on artist (not song or album) similarity.
Four Approaches to Music Recommendations: Pandora, Mufin, Lala, and eMusic
ReadWriteWeb gives us some nice examples of the kinds of recommendation systems I wrote about in my previous post. Pandora is content-based, although the features are extracted by humans. The result is high-quality data, but poor scalability. Mufin is a classical example of content-based music recommenders, using a purely algorithmic approach. Lala seems to be old-fashioned word-of-mouth recommendations put on the Internet. eMusic is a hybrid system, but combines social with expert, and social with content-based like Oscar Celma proposes. Apple Genius is most likely a typical collaborative filtering recommender, based on artist (not song or album) similarity.
Does Everything Really Sound Like Coldplay?
If you have a feeling that all roads somehow lead to Radiohead, you’re not alone. Oscar Celma, my friend and former colleague at the Pompeu Fabra University in Barcelona, successfully defended his PhD thesis on music recommender systems the other day. The thesis, titled “Music Recommendation and Discovery In The Long Tail”, sheds new... Read More »
All hail the information triumvirate!
Wikipedia has come to dominate Google web search results. It often ranks #1 for searches on common topics like Internet and Evolution. Is it true that Wikipedia articles are the very best source of information for all of these topics? Or are we witnessing the effects of a popularity feedback loop, fueled by the principles of least effort, and our tendency to stick with the first and obvious answers? The web link graph is fundamentally a product of socialization, and Google is fundamentally a social search engine. A popularity bias in inherent in all social information systems, leading us all down the same well-trod path. Could it be that, counter to our expectations, the natural dynamic of the web will lead to less diversity in information sources rather than more?
All hail the information triumvirate!
Wikipedia has come to dominate Google web search results. It often ranks #1 for searches on common topics like Internet and Evolution. Is it true that Wikipedia articles are the very best source of information for all of these topics? Or are we witnessing the effects of a popularity feedback loop, fueled by the principles of least effort, and our tendency to stick with the first and obvious answers? The web link graph is fundamentally a product of socialization, and Google is fundamentally a social search engine. A popularity bias in inherent in all social information systems, leading us all down the same well-trod path. Could it be that, counter to our expectations, the natural dynamic of the web will lead to less diversity in information sources rather than more?
Microsoft Surface Enterprise Search Demo at FASTforward’09
A Microsoft Surface Enterprise Search demo is being presented by Conchango on FASTforward’09. Richard Wand writes about their efforts to create a playful search experience, using Microsoft’s new multi-touch screen-table-surface technology. Words like engaging, social and entertaining are not often used to describe enterprise search solutions. So what is different about this demo?
Update: A... Read More »
On-demand Cloud-based Enterprise Search
An interesting discussion is taking place in the Enterprise Search Engine Professionals group on LinkedIn. The question asked is this: Is on-demand cloud based enterprise search a good value proposition for the future (with the recession and companies aggressively cutting cost)?
I have played around in my head with the idea of cloud-based enterprise search... Read More »
Search Design Patterns for Ideas and Inspiration
If your work involves user experience in any way, you should be familiar with design patterns. Bringing patterns into your design will help you define and solve common problems related to user interaction and information architecture. Sharing patterns with your team help you establish a common vocabulary, in turn making it easier to convert... Read More »
Search Inside Obama’s Inaugural Speech
Delve Networks has applied its audio search technology to Obama's inagural speech. When you enter keywords into the search field below the video, those words are highlighted on the timeline, guiding you to the most relevant parts of the video. Audio search is difficult to execute properly, since human speech is imprecise and varies wildly from person to person. Delve Networks have done a good job, however. I'll take a close look at various audio search engines in a future blog post.
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