We present a new compact representation to efficiently store and query large RDF datasets in main memory. Our proposal, called BMatrix, is based on the k2-tree, a data structure devised to represent binary matrices in a compressed way, and aims at improving the results of previous state-of-the-art alternatives, especially in datasets with a relatively large number of predicates. We introduce our technique, together with some improvements on the basic k2-tree that can be applied to our solution in order to boost compression. Experimental results in the flagship RDF dataset DBPedia show that our proposal achieves better compression than existing alternatives, while yielding competitive query times, particularly in the most frequent triple patterns and in queries with unbound predicate, in which we outperform existing solutions.

We introduce a new family of compressed data structures to efficiently store and query large string dictionaries in main memory. Our main technique is a combination of hierarchical Front-coding with ideas from longest-common-prefix computation in suffix arrays. Our data structures yield relevant space-time tradeoffs in real-world dictionaries. We focus on two domains where string dictionaries are extensively used and efficient compression is required: URL collections, a key element in Web graphs and applications such as Web mining; and collections of URIs and literals, the basic components of RDF datasets. Our experiments show that our data structures achieve better compression than the state-of-the-art alternatives while providing very competitive query times.

Although Big RDF management is an emerging topic in the so-called Web of Data, existing techniques disregard the dynamic nature of RDF data. These RDF archives evolve over time and need to be preserved and queried across it. This paper presents v-RDFCSA, an RDF archiving solution that extends RDFCSA (an RDF self-index) to provide version-based queries on top of compressed RDF archives. Our experiments show that v-RDFCSA reduces space requirements up to 35 - 60 times over a state-of-the-art baseline, and gets more than one order of magnitude ahead over it for query resolution.

The eXtensible Markup Language (XML) is acknowledged as the de facto standard for semistructured data representation and data exchange on the Web and many other scenarios. A well-known shortcoming of XML is its verbosity, which increases manipulation, transmission, and processing costs. Various structure-blind and structure-conscious compression techniques can be applied to XML, and some are even access-friendly, meaning that the documents can be efficiently accessed in compressed form. Direct access is necessary to implement the query languages XPath and XQuery, which are the standard ones to exploit the expressiveness of XML. While a good deal of theoretical and practical proposals exist to solve XPath/XQuery operations on XML, only a few ones are well integrated with a compression format that supports the required access operations on the XML data. In this work we go one step further and design a compression format for XML collections that boosts the performance of XPath queries on the data. This is done by designing compressed representations of the XML data that support some complex operations apart from just accessing the data, and those are exploited to solve key components of the XPath queries. Our system, called XXS, is aimed at XML collections containing natural language text, which are compressed to within 35%--50% of their original size while supporting a large subset of XPath operations in time competitive with, and many times outperforming, the best state-of-the-art systems that work on uncompressed representations.

We present in this paper a web-based version of a scrabble game, describing its architecture and some implementation details. This architecture makes possible a high degree of interactivity, so that the players perceive the game as being played in real-time. Furthermore, no client-side plug-in or applet issued. These properties are achieved by means of a carefully designed architecture that uses AJAX (Asynchronous JavaScript and XMLXML) for data exchange. This architecture guarantees low load on the server, so complex computations relative to the game logic can be done in real-time. Moreover, data structures and algorithms were designed to efficiently access a custom Galician dictionary, which supports the game functionalities. We show in this paper how this data structures and algorithms provide an efficient method to create a Scrabble move generation algorithm. We also show how the combination of these with the architecture proposed provides a fully interactive Web application that can handle complex calculations over a very large lexicon with real-time appearance.