Revistas relacionadas con estructura de datos http://dspace.infodocu.lbd.org.es/xmlui/handle/123456789/1396 2026-05-22T19:05:15Z 2026-05-22T19:05:15Z Silva-Coira, Fernando R. Paramá, José de Bernardo, Guillermo Seco, Diego http://dspace.infodocu.lbd.org.es/xmlui/handle/123456789/1426 2025-10-28T02:01:11Z 2019-01-01T00:00:00Z

Space-Efficient Representations of Raster Time Series Silva-Coira, Fernando; R. Paramá, José; de Bernardo, Guillermo; Seco, Diego

2019-01-01T00:00:00Z Nieves R., Brisaboa http://dspace.infodocu.lbd.org.es/xmlui/handle/123456789/1407 2025-10-20T10:59:21Z 2020-01-01T00:00:00Z

Efficient Similarity Search by CombiningIndexing and Caching Strategies Nieves R., Brisaboa A critical issue in large scale search engines is to efficiently handle sudden peaks of incoming query traffic. Research in metric spaces has addressed this problem from the point of view of creating caches that provide information to, if possible, exactly/approximately answer a query very quickly without needing to further process an index. However, one of the problems of that approach is that, if the cache is not able to provide an answer, the distances computed up to that moment are wasted, and the search must proceed through the index structure. In this paper we present an index structure that serves a twofold role: that of a cache and an index in the same structure. In this way, if we are not able to provide a quick approximate answer for the query, the distances computed up to that moment are used to query the index. We present an experimental evaluation of the performance obtained with our structure.

2020-01-01T00:00:00Z Gilberto, Gutiérrez http://dspace.infodocu.lbd.org.es/xmlui/handle/123456789/1405 2025-10-20T11:00:56Z 2023-01-01T00:00:00Z

The largest empty circle with location constraints in spatial databases Gilberto, Gutiérrez Given a set S of points in the two-dimensional space, which are stored in a spatial database, this paper presents an efficient algorithm to find the empty circle, in the area delimited by those points, with the largest area and containing only a query point q. Our algorithm adapts previous work in the field of computational geometry to be used in spatial databases, which require to manage large amounts of data. To achieve this objective, the basic idea is to discard a large part of the points of S, in such a way that the problem can be solved providing only the remaining points to a classical computational geometry algorithm that, by processing a smaller collection of points, saves main memory resources and computation time. The correctness of our algorithm is formally proven. In addition, we empirically show its efficiency and scalability by running a set of experiments using both synthetic and real data.

2023-01-01T00:00:00Z de Bernardo, Guillermo http://dspace.infodocu.lbd.org.es/xmlui/handle/123456789/1401 2025-10-20T11:09:06Z 2021-01-01T00:00:00Z

Compressed and Queryable Self-Indexes for RDF Archives de Bernardo, Guillermo RDF compression and querying are consolidated topics in the Web of Data, with a plethora of solutions to efficiently store and query static datasets. However, as RDF data changes along time, it becomes necessary to keep different versions of RDF datasets, in what is called an RDF archive. For large RDF datasets, naive techniques to store these versions lead to significant scalability problems. In this paper we present v-RDF-SI, one of the first RDF archiving solutions that aims at joining both compression and fast querying. In v-RDF-SI, we extend existing RDF representations based on compact data structures to provide efficient support of version-based queries in compressed space. We present two implementations of v-RDF-SI,named v-RDFCSA and v-HDT, based respectively on RDFCSA (an RDF self-index) and HDT (a W3C-supported compressed RDF representation). We experimentally evaluate v-RDF-SI over a public benchmark named BEAR, showing that v-RDF-SI drastically reduces space requirements.

2021-01-01T00:00:00Z