Efficient and self-tuning incremental query expansion for top-k query processing
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
An efficient and versatile query engine for TopX search
VLDB '05 Proceedings of the 31st international conference on Very large data bases
IO-Top-k: index-access optimized top-k query processing
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Top-k query evaluation with probabilistic guarantees
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
TopX: efficient and versatile top-k query processing for semistructured data
The VLDB Journal — The International Journal on Very Large Data Bases
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This paper describes the setup and results of the Max- Planck-Institut für Informatik's contributions for the INEX 2007 AdHoc Track task. The runs were produced with TopX, a search engine for ranked retrieval of XML data that supports a probabilistic scoring model for full-text content conditions and tag-term combinations, path conditions as exact or relaxable constraints, and ontology-based relaxation of terms and tag names.