Sangam: A Confluence of Knowledge Streams

Improving Search Engine Performance Through Dynamic Caching

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dc.creator Gutierrez-Soto, C
dc.creator Palomino, MA
dc.creator Roa, E
dc.creator Galdames, P
dc.date 2022-03-07T15:54:44Z
dc.date 2022-03-07T15:54:44Z
dc.date 2021-01-01
dc.date.accessioned 2022-05-26T21:09:40Z
dc.date.available 2022-05-26T21:09:40Z
dc.identifier 9781665409568
dc.identifier 1522-4902
dc.identifier http://hdl.handle.net/10026.1/18910
dc.identifier 10.1109/SCCC54552.2021.9650412
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/228962
dc.description Web search engines process several millions of queries per second over several billions of documents. Without any optimization, this process can be very expensive in terms of processing times. In this regard, appropriate use of computing power is essential. One way to tackle this problem is through the use of caching mechanisms. Keep in mind, most research based on caching mechanisms uses repetitive queries-it means queries syntactically equals-to conform caches. Furthermore, the universe of repetitive queries is small in comparison with a set of similar semantically queries. This paper presents a dynamic cache that relies on an online algorithm, which performs a semantic match between the user's query and queries stored in the cache. Broadly speaking, the algorithm employs a priority queue, where popular queries are stored along with their relevant documents. Empirical results show that our proposed approach improves the response times and precision. Moreover, the use of semantically related keywords proves to be a key contribution that had been overlooked in previous research.
dc.language en
dc.relation ISSN:1522-4902
dc.rights Not known
dc.title Improving Search Engine Performance Through Dynamic Caching
dc.type Conference Contribution


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