2006 BayesianSets
- (Ghahramani & Heller, 2006) ⇒ Zoubin Ghahramani, Katherine A. Heller. (2006). “Bayesian Sets.” In: Advances in Neural Information Processing Systems (NIPS 2006).
Subject Headings: Set Expansion Task.
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Abstract
Inspired by “Google™ Sets”, we consider the problem of retrieving items from a concept or cluster, given a query consisting of a few items from that cluster. We formulate this as a Bayesian inference problem and describe a very simple algorithm for solving it. Our algorithm uses a model-based concept of a cluster and ranks items using a score which evaluates the marginal probability that each item belongs to a cluster containing the query items. For exponential family models with conjugate priors this marginal probability is a simple function of sufficient statistics. We focus on sparse binary data and show that our score can be evaluated exactly using a single sparse matrix multiplication, making it possible to apply our algorithm to very large datasets. We evaluate our algorithm on three datasets: retrieving movies from EachMovie, finding completions of author sets from the NIPS dataset, and finding completions of sets of words appearing in the Grolier encyclopedia. We compare to Google™ Sets and show that Bayesian Sets gives very reasonable set completions.
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2006 BayesianSets | Zoubin Ghahramani Katherine A. Heller | Bayesian Sets | http://books.nips.cc/papers/files/nips18/NIPS2005 0712.pdf |