Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

7

ALT
2008
Springer

favoriteEmaildiscussreport

136views Machine Learning» more ALT 2008»

Clustering with Interactive Feedback

14 years 1 months ago

Clustering with Interactive Feedback

Download www.cc.gatech.edu

In this paper, we initiate a theoretical study of the problem of clustering data under interactive feedback. We introduce a query-based model in which users can provide feedback to a clustering algorithm in a natural way via split and merge requests. We then analyze the “clusterability” of diﬀerent concept classes in this framework — the ability to cluster correctly with a bounded number of requests under only the assumption that each cluster can be described by a concept in the class — and provide eﬃcient algorithms as well as information-theoretic upper and lower bounds.

Maria-Florina Balcan, Avrim Blum

Real-time Traffic

ALT 2008 | Clustering Algorithm | Diﬀerent Concept Classes | Machine Learning | Query-based Model |

claim paper

Related Content

» Interactive Clustering of Video Segments for Media Structuring

» A ClusterLevel Semisupervision Model for Interactive Clustering

» A Study of SelfOrganizing Map in Interactive Relevance Feedback

» A Cluster Based Pseudo Feedback Technique Which Exploits Good and Bad Clusters

» Text clustering with extended user feedback

» Which Clustering Do You Want Inducing Your Ideal Clustering with Minimal Feedback

» Evaluating Document Clustering for Interactive Information Retrieval

» Discovering interesting patterns through users interactive feedback

» An Interactive RegionBased Image Clustering and Retrieval Platform

Post Info
More Details (n/a)

Added	14 Mar 2010
Updated	14 Mar 2010
Type	Conference
Year	2008
Where	ALT
Authors	Maria-Florina Balcan, Avrim Blum

Comments (0)