Abstract
Negated query terms allow documents containing such terms to be filtered out of a search results list, supporting disambiguation. In this work, the effect of negation on the efficiency of disjunctive, top-k retrieval is examined. First, we show how negation can be integrated efficiently into two popular dynamic pruning algorithms. Then, we explore the efficiency of our approach, and show that while often efficient, negation can negatively impact the dynamic pruning effectiveness for certain queries.
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CITATION STYLE
Mackenzie, J., Macdonald, C., Scholer, F., & Culpepper, J. S. (2018). On the cost of negation for dynamic pruning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10772 LNCS, pp. 544–549). Springer Verlag. https://doi.org/10.1007/978-3-319-76941-7_42
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