INextCube: Information networkenhanced text cube

Yintao Yu, Cindy X. Lin, Yizhou Sun, Chen Chen, Jiawei Han, Binbin Liao, Tianyi Wu, Chengxiang Zhai, Duo Zhang, Bo Zhao

Research output: Contribution to journalArticlepeer-review

Abstract

Nowadays, most business, administration, and/or scientic databases contain both structured attributes and text attributes. We call a database that consists of both multidi-mensional structured data and narrative text data as multidimensional text database. Searching, OLAP, and mining such databases pose many research challenges. To enhance the power of data analysis, interesting entities and relation-ships can be extracted from such databases to derive hetero-geneous information networks, which in turn will substantially increase the power and flexibility of data exploration in such databases. Based on our previous studies on TextCube [1], TopicCube [2], and information network analysis, such as RankClus [3] and NetClus [4], we construct iNextCube, an information-Network-enhanced text Cube. In this demo, we show the power of iNextCube in the search and analysis of two multidimensional text databases: (i) a DBLP-based CS bibliographic database, and (ii) an online news database.

Original languageEnglish (US)
Pages (from-to)1622-1625
Number of pages4
JournalProceedings of the VLDB Endowment
Volume2
Issue number2
DOIs
StatePublished - Aug 2009

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science(all)

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