DBPubs: Multidimensional exploration of database publications

Akanksha Baid, Andrey Balmin, Heasoo Hwang, Erik Nijkamp, Jun Rao, Berthold Reinwald, Alkis Simitsis, Yannis Sismanis, Frank van Ham

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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.

Original languageEnglish
Pages (from-to)1456-1459
Number of pages4
JournalProceedings of the VLDB Endowment
Issue number2
StatePublished - Aug 2008


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