Sciweavers

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

22

ADMA
2007
Springer

favoriteEmaildiscussreport

106views Data Mining» more ADMA 2007»

Topic Extraction with AGAPE

14 years 1 months ago

Topic Extraction with AGAPE

Download eric.univ-lyon2.fr

This paper uses an optimization approach to address the problem of conceptual clustering. The aim of AGAPE, which is based on the tabu-search meta-heuristic using split, merge and a special “k-means” move, is to extract concepts by optimizing a global quality function. It is deterministic and uses no a priori knowledge about the number of clusters. Experiments carried out in topic extraction show very promising results on both artiﬁcial and real datasets.

Julien Velcin, Jean-Gabriel Ganascia

Real-time Traffic

ADMA 2007 | Conceptual Clustering | Data Mining | Global Quality Function | Optimization Approach |

claim paper

Related Content

» CrossLingual Latent Topic Extraction

» Automatic Keyphrase Extraction via Topic Decomposition

» CrossDomain CoExtraction of Sentiment and Topic Lexicons

» Relation Extraction with Relation Topics

» Pattern Learning for Relation Extraction with a Hierarchical Topic Model

» Hierarchical Taxonomy Extraction by Mining Topical Query Sessions

» Topical Keyphrase Extraction from Twitter

» Discovery of Topically Coherent Sentences for Extractive Summarization

» A Latent Topic Extracting Method based on Events in a Document and its Application

Post Info
More Details (n/a)

Added	06 Jun 2010
Updated	06 Jun 2010
Type	Conference
Year	2007
Where	ADMA
Authors	Julien Velcin, Jean-Gabriel Ganascia

Comments (0)