Abstract
Tag-based browsing is a popular interaction model for navigating digital libraries. According to this model, users select descriptive tags to filter resources in the collections. Typical implementations of the model are based on inverted indexes. However, these implementations can require a considerable amount of set operations to update the browsing state. To palliate this inconvenience, it is possible to adopt suitable cache strategies. In this paper we describe and compare two of these strategies: (i) a query-based strategy, according to which previously computed browsing states are indexed by sets of selected tags; and (ii) a resource-based strategy, according to which browsing states are indexed by sets of filtered resources. Our comparison focused on runtime performance, and was carried out empirically, using a real-world web-based collection in the field of digital humanities. The results obtained show that the resource-based strategy clearly outperforms the query-based one.
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Notes
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All the measures reported were taken on a machine with an Intel® Core™ i5-4660S 2.9 GHz processor, RAM 16 GB and Windows 10 OS. Browsing software was programmed in Java. The browsing cache was maintained in memory using Java’s HashMap s. Sets were managed using roaring bitmaps [4].
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Acknowledgements
This research is supported by the research projects TIN2014-52010-R and TIN2017-88092-R. Also, we would like to thank Mercedes Guinea and Alfredo Fernández-Valmayor (El Caño Foundation, Panamá), for their work on Chasqui.
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Gayoso-Cabada, J., Gómez-Albarrán, M., Sierra, JL. (2018). Query-Based Versus Resource-Based Cache Strategies in Tag-Based Browsing Systems. In: Dobreva, M., Hinze, A., Žumer, M. (eds) Maturity and Innovation in Digital Libraries. ICADL 2018. Lecture Notes in Computer Science(), vol 11279. Springer, Cham. https://doi.org/10.1007/978-3-030-04257-8_4
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