Fast and Reliable Online Learning to Rank for Information Retrieval

Add to your list(s) Download to your calendar using vCal

• Katja Hofmann, University of Amsterdam
• Monday 24 September 2012, 10:00-11:00
• Small lecture theatre, Microsoft Research Ltd, 7 J J Thomson Avenue (Off Madingley Road), Cambridge.

If you have a question about this talk, please contact Microsoft Research Cambridge Talks Admins.

o This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attendin

Online learning to rank for information retrieval (IR) holds promise for allowing the development of “self-learning search engines” that can automatically adjust to their users. With the large amount of e.g., click data that can be collected in web search settings, such techniques could enable highly scalable ranking optimization. However, feedback obtained from user interactions is noisy, and developing approaches that can learn from this feedback quickly and reliably is a major challenge.

In this talk I will present my recent work, which addresses the challenges posed by learning from natural user interactions. First, I will detail a new method, called Probabilistic Interleave, for inferring user preferences from users’ clicks on search results. I show that this method allows unbiased and fine-grained ranker comparison using noisy click data, and that this is the first such method that allows the effective reuse of historical data (i.e., collected for previous comparisons) to infer information about new rankers. Second, I show that Probabilistic Interleave enables new online learning to rank approaches that can reuse historical interaction data to speed up learning by several orders of magnitude, especially under high levels of noise in user feedback. I conclude with an outlook on research directions in online learning to rank for IR, that are opened up by our results.

This talk is part of the Microsoft Research Cambridge, public talks series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Cambridge Big Data
• Cambridge University Engineering Department Talks
• Centre for Smart Infrastructure & Construction
• Chris Davis' list
• Featured lists
• Guy Emerson's list
• Interested Talks
• Methodology in design research
• Microsoft Research Cambridge, public talks
• PMRFPS's
• School of Technology
• Small lecture theatre, Microsoft Research Ltd, 7 J J Thomson Avenue (Off Madingley Road), Cambridge
• Trust & Technology Initiative - interesting events
• bld31
• ndk22's list
• personal list
• rp587

Note that ex-directory lists are not shown.