Showing posts with label personalized search. Show all posts
Showing posts with label personalized search. Show all posts

Wednesday, October 17, 2007

Attention IR and People Search

The SIGIR 2007 conference also had a couple of gems in the Doctoral Consortium workshop.

Krisztian Balog (University of Amsterdam) homepage
People Search in the Enterprise

The abstract of Balog looked a two areas concerning people search, profiling people and enabling search of those people based upon both the topical and social profile. Who is an expert on X? Who do I know (or get introduced to) someone who is an expert on X? His research seems to be just beginning.. I'll be checking his page for new papers.

Georg Buscher (German Research Center for AI) homepage
Attention-Based Information Retrieval

Buscher won the best presentation award at the workshop. His slides outline how attention data can be used to bias/rerank IR results to enable re-finding old information/documents as well as doing query expansion (profile based???) given the current user's attention data. His research is also fairly new.

Both of these topics are obviously of interest to Others Online and the idea of connecting people together through a common topic or set of topics that are learned as implicitly related to the users.

Monday, September 10, 2007

The Implicit Web flowing into Collective Search

Here are some recent articles that I read and kept thinking about again and again. What is cool about this moment in time is that these things are gelling. Entrepreneurs and innovators are trying to build this stuff, rather than the ideas rotting unfulfilled in the mind of some AI/Search-Engine geek.

Read/Write Web's Implicit Web

Important point here is that systems should both learn what users are interested in implicitly and allow users control over the learned topics. The former point is what algorithms like collaborative filtering were intended to do. The latter is a great point that users should have visibility and control into their learned topics.

This has been a frequent critique against Amazon's recommender system.. while personalized, it can learn goofy things. I have no desire to be a frequent buyer of items similar to what I bought for a niece as a gift last year.

Collective Search by Greg Linden

I just learned that Greg is one of the brains behind Amazon's AI. Thinking about the data Amazon has and what could be done with it always makes me drool. Greg's post here is an aggregation of points he came up with while reading transcripts of the recent SES 2007 conference.

I'll join Ask's Jim Lanzone (isn't the new Ask.com much better than Google!) in saying that collective search is potentially better than personalized search. Greg is arguing for a redefinition of 'personalization' here, but we have to pick descriptive terms for abstract ideas. I would define personalization as skewing of search results by what you are interested in. Where I'd read collective search as letting the collective behaviors of a group of similar users influence/skew search results. This is the flavor of stuff I worked on at RightNow.

Ultimate Answer Engine @ Information Week

Favorite quote: "Who said an edit box and 10 blue links is what search is?" asks Microsoft's Satya Nadella.

This great piece has several items that just jumped out at me. "Queryless Search", essentially this is using what the system knows about you and your path through to the engine and do a implicit query. (We also worked and patented variations of this idea at RightNow). The "Personalization" and "Social Skills" sections deal with the ideas in Greg's post above. More to come on that re 'The Social Graph'.

Another good quote: "Serendipity is an amazing teacher". This is what Others Online is all about... focused on People, not necessarily documents/media.

After reading all three of these in the current context of what people are willing to spend time and money on... I can't help but be totally jacked about the opportunities at hand!

Loads of academics have been working on this stuff for years, check out any ACM SIGIR and various data mining conference proceedings for the last 10+ years. Personally, I've been thinking and working on many of the things above since 2000 when Doug Warner and I started doing a deep dive into the academic literature.