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Data clouds: summarizing keyword search results over structured data
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Source Extending Database Technology; Vol. 360 archive
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology table of contents
Saint Petersburg, Russia
SESSION: Research sessions: Database summarization table of contents
Pages 391-402  
Year of Publication: 2009
ISBN:978-1-60558-422-5
Authors
Georgia Koutrika  Stanford University, Stanford, CA
Zahra Mohammadi Zadeh  Stanford University, Stanford, CA
Hector Garcia-Molina  Stanford University, Stanford, CA
Publisher
ACM  New York, NY, USA
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ABSTRACT

Keyword searches are attractive because they facilitate users searching structured databases. On the other hand, tag clouds are popular for navigation and visualization purposes over unstructured data because they can highlight the most significant concepts and hidden relationships in the underlying content dynamically. In this paper, we propose coupling the flexibility of keyword searches over structured data with the summarization and navigation capabilities of tag clouds to help users access a database. We propose using clouds over structured data (data clouds) to summarize the results of keyword searches over structured data and to guide users to refine their searches. The cloud presents the most significant words associated with the search results. Our keyword search model allows searching for entities than can span multiple tables in the database rather than just tuples, as existing keyword searches over databases do. We present several methods to compute the scores both for the entities and for the terms in the search results. We describe algorithms for keyword searches with data clouds and we present our system, CourseCloud, that offers a unified search and browse interface to a course database. We present experimental results showing (a) the appropriateness of the methods used for scoring terms, (b) the performance of the proposed algorithms, and (c) the effectiveness of CourseCloud compared to typical search and browse interfaces to a course database.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Georgia Koutrika: colleagues
Zahra Mohammadi Zadeh: colleagues
Hector Garcia-Molina: colleagues