Pattern based processing of XPath queries

As the popularity of areas including document storage and distributed systems continues to grow, the demand for high performance XML databases is increasingly evident. This has led to a number of research eorts aimed at exploiting the maturity of relational database systems in order to in- crease XML query performance. In our approach, we use an index structure based on a metamodel for XML databases combined with relational database technology to facilitate fast access to XML document elements. The query process involves transforming XPath expressions to SQL which can be executed over our optimised query engine. As there are many dierent types of XPath queries, varying processing logic may be applied to boost performance not only to indi- vidual XPath axes, but across multiple axes simultaneously. This paper describes a pattern based approach to XPath query processing, which permits the execution of a group of XPath location steps in parallel

DescribeX: A Framework for Exploring and Querying XML Web Collections

This thesis introduces DescribeX, a powerful framework that is capable of describing arbitrarily complex XML summaries of web collections, providing support for more efficient evaluation of XPath workloads. DescribeX permits the declarative description of document structure using all axes and language constructs in XPath, and generalizes many of the XML indexing and summarization approaches in the literature. DescribeX supports the construction of heterogeneous summaries where different document elements sharing a common structure can be declaratively defined and refined by means of path regular expressions on axes, or axis path regular expression (AxPREs). DescribeX can significantly help in the understanding of both the structure of complex, heterogeneous XML collections and the behaviour of XPath queries evaluated on them. Experimental results demonstrate the scalability of DescribeX summary refinements and stabilizations (the key enablers for tailoring summaries) with multi-gigabyte web collections. A comparative study suggests that using a DescribeX summary created from a given workload can produce query evaluation times orders of magnitude better than using existing summaries. DescribeX's light-weight approach of combining summaries with a file-at-a-time XPath processor can be a very competitive alternative, in terms of performance, to conventional fully-fledged XML query engines that provide DB-like functionality such as security, transaction processing, and native storage.Comment: PhD thesis, University of Toronto, 2008, 163 page

SIQXC: Schema Independent Queryable XML Compression for Smartphones

The explosive growth of XML use over the last decade has led to a lot of research on how to best store and access it. This growth has resulted in XML being described as a de facto standard for storage and exchange of data over the web. However, XML has high redundancy because of its self-­‐ describing nature making it verbose. The verbose nature of XML poses a storage problem. This has led to much research devoted to XML compression. It has become of more interest since the use of resource constrained devices is also on the rise. These devices are limited in storage space, processing power and also have finite energy. Therefore, these devices cannot cope with storing and processing large XML documents. XML queryable compression methods could be a solution but none of them has a query processor that runs on such devices. Currently, wireless connections are used to alleviate the problem but they have adverse effects on the battery life. They are therefore not a sustainable solution. This thesis describes an attempt to address this problem by proposing a queryable compressor (SIQXC) with a query processor that runs in a resource constrained environment thereby lowering wireless connection dependency yet alleviating the storage problem. It applies a novel simple 2 tuple integer encoding system, clustering and gzip. SIQXC achieves an average compression ratio of 70% which is higher than most queryable XML compressors and also supports a wide range of XPATH operators making it competitive approach. It was tested through a practical implementation evaluated against the real data that is usually used for XML benchmarking. The evaluation covered the compression ratio, compression time and query evaluation accuracy and response time. SIQXC allows users to some extent locally store and manipulate the otherwise verbose XML on their Smartphones

Querying Large Collections of Semistructured Data

An increasing amount of data is published as semistructured documents formatted with presentational markup. Examples include data objects such as mathematical expressions encoded with MathML or web pages encoded with XHTML. Our intention is to improve the state of the art in retrieving, manipulating, or mining such data. We focus first on mathematics retrieval, which is appealing in various domains, such as education, digital libraries, engineering, patent documents, and medical sciences. Capturing the similarity of mathematical expressions also greatly enhances document classification in such domains. Unlike text retrieval, where keywords carry enough semantics to distinguish text documents and rank them, math symbols do not contain much semantic information on their own. Unfortunately, considering the structure of mathematical expressions to calculate relevance scores of documents results in ranking algorithms that are computationally more expensive than the typical ranking algorithms employed for text documents. As a result, current math retrieval systems either limit themselves to exact matches, or they ignore the structure completely; they sacrifice either recall or precision for efficiency. We propose instead an efficient end-to-end math retrieval system based on a structural similarity ranking algorithm. We describe novel optimization techniques to reduce the index size and the query processing time. Thus, with the proposed optimizations, mathematical contents can be fully exploited to rank documents in response to mathematical queries. We demonstrate the effectiveness and the efficiency of our solution experimentally, using a special-purpose testbed that we developed for evaluating math retrieval systems. We finally extend our retrieval system to accommodate rich queries that consist of combinations of math expressions and textual keywords. As a second focal point, we address the problem of recognizing structural repetitions in typical web documents. Most web pages use presentational markup standards, in which the tags control the formatting of documents rather than semantically describing their contents. Hence, their structures typically contain more irregularities than descriptive (data-oriented) markup languages. Even though applications would greatly benefit from a grammar inference algorithm that captures structure to make it explicit, the existing algorithms for XML schema inference, which target data-oriented markup, are ineffective in inferring grammars for web documents with presentational markup. There is currently no general-purpose grammar inference framework that can handle irregularities commonly found in web documents and that can operate with only a few examples. Although inferring grammars for individual web pages has been partially addressed by data extraction tools, the existing solutions rely on simplifying assumptions that limit their application. Hence, we describe a principled approach to the problem by defining a class of grammars that can be inferred from very small sample sets and can capture the structure of most web documents. The effectiveness of this approach, together with a comparison against various classes of grammars including DTDs and XSDs, is demonstrated through extensive experiments on web documents. We finally use the proposed grammar inference framework to extend our math retrieval system and to optimize it further

Contribution à l'interrogation flexible et personnalisée d'objets complexes modélisés par des graphes

Plusieurs domaines d'application traitent des objets et des données complexes dont la structure et la sémantique de leurs composants sont des informations importantes pour leur manipulation et leur exploitation. La structure de graphe a été bien souvent adoptée, comme modèles de représentation, dans ces domaines. Elle permet de véhiculer un maximum d'informations, liées à la structure, la sémantique et au comportement de ces objets, nécessaires pour assurer une meilleure représentation et une manipulation e cace. Ainsi, lors d'une comparaison entre deux objets complexes, l'opération d'appariement est appliquée entre les graphes les modélisant. Nous nous sommes intéressés dans cette thèse à l'appariement approximatif qui permet de sélectionner les graphes les plus similaires au graphe d'une requête. L'objectif de notre travail est de contribuer à l'interrogation exible et personnalisée d'objets complexes modélisés sous forme de graphes pour identi er les graphes les plus pertinents aux besoins de l'utilisateur, exprimés d'une manière partielle ou imprécise. Dans un premier temps, nous avons proposé un cadre de sélection de services Web modélisés sous forme de graphes qui permet (i) d'améliorer le processus d'appariement en intégrant les préférences des utilisateurs et l'aspect structurel des graphes comparés, et (ii) de retourner les services les plus pertinents. Une deuxième méthode d'évaluation de requêtes de recherche de graphes par similarité a également été présentée pour calculer le skyline de graphes d'une requête utilisateur en tenant compte de plusieurs mesures de distance de graphes. En n, des approches de ra nement ont été dé nies pour réduire la taille, souvent importante, du skyline. Elles ont pour but d'identi er et d'ordonner les points skyline qui répondent le mieux à la requête de l'utilisateur.Several application domains deal with complex objects whose structure and semantics of their components are crucial for their handling. For this, graph structure has been adopted, as a model of representation, in these areas to capture a maximum of information, related to the structure, semantics and behavior of such objects, necessary for e ective representation and processing. Thus, when comparing two complex objects, a matching technique is applied between their graph structures. In this thesis, we are interested in approximate matching techniques which constitute suitable tools to automatically nd and select the most similar graphs to user graph query. The aim of our work is to develop methods to personalized and exible querying of repositories of complex objects modeled thanks to graphs and then to return the graphs results that t best the users needs, often expressed partially and in an imprecise way. In a rst time, we propose a exible approach for Web service retrieval that relies both on preference satis ability and structural similarity between process model graphs. This approach allows (i) to improve the matching process by integrating user preferences and the graph structural aspect, and (ii) to return the most relevant services. A second method for evaluating graph similarity queries is also presented. It retrieves graph similarity skyline of a user query by considering a vector of several graph distance measures instead of a single measure. Thus, graphs which are maximally similar to graph query are returned in an ordered way. Finally, re nement methods have been developed to reduce the size of the skyline when it is of a signi cant size. They aim to identify and order skyline points that match best the user query.RENNES1-Bibl. électronique (352382106) / SudocSudocFranceF

FIX: Feature-based Indexing Technique for XML Documents

Indexing large XML databases is crucial for efficient evaluation of XML twig queries. In this paper, we propose a feature-based indexing technique, called FIX, based on spectral graph theory. The basic idea is that for each twig pattern in a collection of XML documents, we calculate a vector of features based on its structural properties. These features are used as keys for the patterns and stored in a B + tree. Given an XPath query, its feature vector is first calculated and looked up in the index. Then a further refinement phase is performed to fetch the final results. We experimentally study the indexing technique over both synthetic and real data sets. Our experiments show that FIX provides great pruning power and could gain an order of magnitude performance improvement for many XPath queries over existing evaluation techniques

SECURING XML DOCUMENTS

XML (extensible markup language) is becoming the current standard for establishing interoperability on the Web. XML data are self-descriptive and syntax-extensible; this makes it very suitable for representation and exchange of semi-structured data, and allows users to define new elements for their specific applications. As a result, the number of documents incorporating this standard is continuously increasing over the Web. The processing of XML documents may require a traversal of all document structure and therefore, the cost could be very high. A strong demand for a means of efficient and effective XML processing has posed a new challenge for the database world. This paper discusses a fast and efficient indexing technique for XML documents, and introduces the XML graph numbering scheme. It can be used for indexing and securing graph structure of XML documents. This technique provides an efficient method to speed up XML data processing. Furthermore, the paper explores the classification of existing methods impact of query processing, and indexing