Abstract
Autocompletion services help users in formulating queries by exploiting past queries. In this paper we propose methods for improving such services; specifically methods for increasing the number and the quality of the suggested “completions”. In particular, we propose a novel method for partitioning the internal data structure that keeps the suggestions, making autocompletion services more scalable and faster. In addition we introduce a ranking method which promotes a suggestion that can lead to many other suggestions. The experimental and empirical results are promising.
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Kastrinakis, D., Tzitzikas, Y. (2010). Advancing Search Query Autocompletion Services with More and Better Suggestions. In: Benatallah, B., Casati, F., Kappel, G., Rossi, G. (eds) Web Engineering. ICWE 2010. Lecture Notes in Computer Science, vol 6189. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13911-6_3
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DOI: https://doi.org/10.1007/978-3-642-13911-6_3
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