DBPubs: Multidimensional Exploration of Database Publications

被引:3
|
作者
Baid, Akanksha [2 ]
Balmin, Andrey [1 ]
Hwang, Heasoo [3 ]
Nijkamp, Erik [4 ]
Rao, Jun [1 ]
Reinwald, Berthold [1 ]
Simitsis, Alkis [1 ]
Sismanis, Yannis [1 ]
van Hams, Frank [5 ]
机构
[1] IBM Almaden RC, San Jose, CA USA
[2] Univ Wisconsin, Madison, WI 53706 USA
[3] Univ Calif San Diego, La Jolla, CA USA
[4] IBM Germany, Ehningen, Germany
[5] IBM Res, Cambridge, MA USA
来源
PROCEEDINGS OF THE VLDB ENDOWMENT | 2008年 / 1卷 / 02期
关键词
Publishing;
D O I
10.14778/1454159.1454199
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
DBPubs is a system for effectively analyzing and exploring the content of database publications by combining keyword search with OLAP-style aggregations, navigation, and reporting. DBPubs starts with keyword search over the content of publications. The publications' metadata such as title, authors, venues, year, and so on, provide traditional OLAP static dimensions, which are combined with dynamic dimensions discovered from the content of the publications in the search result, such as frequent phrases, relevant phrases, and topics. We compute publication ranks based on the link structure between documents, i.e., citations, and aggregate them to find seminal papers, discover trends, and rank authors. We deploy an OLAP tool for multidimensional content exploration through traditional OLAP rollup-drilldown operations on the static and dynamic dimensions, solutions for multi-cube analysis, dynamic navigation of the content, and highlighting of interesting dices of the multidimensional content dataspace.
引用
收藏
页码:1456 / 1459
页数:4
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