The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Scaling personalized web search
WWW '03 Proceedings of the 12th international conference on World Wide Web
ManyEyes: a Site for Visualization at Internet Scale
IEEE Transactions on Visualization and Computer Graphics
Objectrank: authority-based keyword search in databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Multidimensional content eXploration
Proceedings of the VLDB Endowment
Multidimensional content eXploration
Proceedings of the VLDB Endowment
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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.