Paper Search Console

Home Search Page Alphabetical List About Contact

Journal Title

Title of Journal: Data Min Knowl Disc

Search In Journal Title:

Abbravation: Data Mining and Knowledge Discovery

Search In Journal Abbravation:

Publisher

Springer US

Search In Publisher:

DOI

10.1007/978-3-7091-0205-3

Search In DOI:

ISSN

1573-756X

Search In ISSN:
Search In Title Of Papers:

CrossClus: user-guided multi-relational clustering

Authors: Xiaoxin Yin, Jiawei Han, Philip S. Yu,

Publish Date: 2007/07/06
Volume: 15, Issue:3, Pages: 321-348
PDF Link

Abstract

Most structured data in real-life applications are stored in relational databases containing multiple semantically linked relations. Unlike clustering in a single table, when clustering objects in relational databases there are usually a large number of features conveying very different semantic information, and using all features indiscriminately is unlikely to generate meaningful results. Because the user knows her goal of clustering, we propose a new approach called CrossClus, which performs multi-relational clustering under user’s guidance. Unlike semi-supervised clustering which requires the user to provide a training set, we minimize the user’s effort by using a very simple form of user guidance. The user is only required to select one or a small set of features that are pertinent to the clustering goal, and CrossClus searches for other pertinent features in multiple relations. Each feature is evaluated by whether it clusters objects in a similar way with the user specified features. We design efficient and accurate approaches for both feature selection and object clustering. Our comprehensive experiments demonstrate the effectiveness and scalability of CrossClus.The work was supported in part by the U.S. National Science Foundation NSF IIS-03-13678 and NSF BDI-05-15813, and an IBM Faculty Award. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect views of the funding agencies.


Keywords:

References


.
Search In Abstract Of Papers:
Other Papers In This Journal:


Search Result:



Help video to use 'Paper Search Console'