Mining knowledge from databases: An information network analysis approach

Jiawei Han, Yizhou Sun, Xifeng Yan, Philip S. Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most people consider a database is merely a data repository that supports data storage and retrieval. Actually, a database contains rich, inter-related, multi-typed data and information, forming one or a set of gigantic, interconnected, heterogeneous information networks. Much knowledge can be derived from such information networks if we systematically develop an effective and scalable database-oriented information network analysis technology. In this tutorial, we introduce database-oriented information network analysis methods and demonstrate how information networks can be used to improve data quality and consistency, facilitate data integration, and generate interesting knowledge. This tutorial presents an organized picture on how to turn a database into one or a set of organized heterogeneous information networks, how information networks can be used for data cleaning, data consolidation, and data qualify improvement, how to discover various kinds of knowledge from information networks, how to perform OLAP in information networks, and how to transform database data into knowledge by information network analysis. Moreover, we present interesting case studies on real datasets, including DBLP and Flickr, and show how interesting and organized knowledge can be generated from database-oriented information networks.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 International Conference on Management of Data, SIGMOD '10
Pages1251-1252
Number of pages2
DOIs
StatePublished - 2010
Event2010 International Conference on Management of Data, SIGMOD '10 - Indianapolis, IN, United States
Duration: Jun 6 2010Jun 11 2010

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Other

Other2010 International Conference on Management of Data, SIGMOD '10
CountryUnited States
CityIndianapolis, IN
Period6/6/106/11/10

Keywords

  • data mining
  • information networks
  • link analysis

ASJC Scopus subject areas

  • Software
  • Information Systems

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