Sihem Amer-Yahia

Minimization of tree pattern queries

Tree patterns forms a natural basis to query tree-structured data such as XML and LDAP. Since the efficiency of tree pattern matching against a tree-structured database depends on the size of the pattern, it is essential to identify and eliminate redundant nodes in the pattern and do so as quickly as possible. In this paper, we study tree pattern minimization both in the absence and in the presence of integrity constraints (ICs) on the underlying tree-structured database.nWhen no ICs are considered, we call the process of minimizing a tree pattern, constraint-independent minimization. We develop a polynomial time algorithm called CIM for this purpose. CIMs efficiency stems from two key properties: (i) a node cannot be redundant unless its children are, and (ii) the order of elimination of redundant nodes is immaterial. When ICs are considered for minimization, we refer to it as constraint-dependent minimization. For tree-structured databases, required child/descendant and type co-occurrence ICs are very natural. Under such ICs, we show that the minimal equivalent query is unique. We show the surprising result that the algorithm obtained by first augmenting the tree pattern using ICS, and then applying CIM, always finds the unique minimal equivalent query; we refer to this algorithm as ACIM. While ACIM is also polynomial time, it can be expensive in practice because of its inherent non-locality. We then present a fast algorithm, CDM, that identifies and eliminates local redundancies due to ICs, based on propagating “information labels” up the tree pattern. CDM can be applied prior to ACIM for improving the minimization efficiency. We complement our analytical results with an experimental study that shows the effectiveness of our tree pattern minimization techniques.

FleXPath: flexible structure and full-text querying for XML

Querying XML data is a well-explored topic with powerful database-style query languages such as XPath and XQuery set to become W3C standards. An equally compelling paradigm for querying XML documents is full-text search on textual content. In this paper, we study fundamental challenges that arise when we try to integrate these two querying paradigms.While keyword search is based on approximate matching, XPath has exact match semantics. We address this mismatch by considering queries on structure as a template, and looking for answers that best match this template and the full-text search. To achieve this, we provide an elegant definition of relaxation on structure and define primitive operators to span the space of relaxations. Query answering is now based on ranking potential answers on structural and full-text search conditions. We set out certain desirable principles for ranking schemes and propose natural ranking schemes that adhere to these principles. We develop efficient algorithms for answering top-K queries and discuss results from a comprehensive set of experiments that demonstrate the utility and scalability of the proposed framework and algorithms.

Tree Pattern Relaxation

Tree patterns are fundamental to querying tree-structured data like XML. Because of the heterogeneity of XML data, it is often more appropriate to permit approximate query matching and return ranked answers, in the spirit of Information Retrieval, than to return only exact answers. In this paper, we study the problem of approximate XML query matching, based on tree pattern relaxations, and devise efficient algorithms to evaluate relaxed tree patterns. We consider weighted tree patterns, where exact and relaxed weights, associated with nodes and edges of the tree pattern, are used to compute the scores of query answers. We are interested in the problem of finding answers whose scores are at least as large as a given threshold. We design data pruning algorithms where intermediate query results are filtered dynamically during the evaluation process. We develop anoptimization that exploits scores of intermediate results to improve query evaluation efficiency. Finally, we show experimentally that our techniques outperform rewriting-based and post-pruning strategies.

Texquery: a full-text search extension to xquery

One of the key benefits of XML is its ability to represent a mix of structured and unstructured (text) data. Although current XML query languages such as XPath and XQuery can express rich queries over structured data, they can only express very rudimentary queries over text data. We thus propose TeXQuery, which is a powerful full-text search extension to XQuery. TeXQuery provides a rich set of fully composable full-text search primitives,such as Boolean connectives, phrase matching, proximity distance, stemming and thesauri. TeXQuery also enables users to seamlessly query over both structured and text data by embedding TeXQuery primitives in XQuery, and vice versa. Finally, TeXQuery supports a flexible scoring construct that can be used toscore query results based on full-text predicates. TeXQuery is the precursor ofthe full-text language extensions to XPath 2.0 and XQuery 1.0 currently being developed by the W3C.

Tree pattern query minimization

Abstract. Tree patterns form a natural basis to query tree-structured data such as XML and LDAP. To improve the efficiency of tree pattern matching, it is essential to quickly identify and eliminate redundant nodes in the pattern. In this paper, we study tree pattern minimization both in the absence and in the presence of integrity constraints (ICs) on the underlying tree-structured database. In the absence of ICs, we develop a polynomial-time query minimization algorithm called CIM, whose efficiency stems from two key properties: (i) a node cannot be redundant unless its children are; and (ii) the order of elimination of redundant nodes is immaterial. When ICs are considered for minimization, we develop a technique for query minimization based on three fundamental operations: augmentation (an adaptation of the well-known chase procedure), minimization (based on homomorphism techniques), and reduction. We show the surprising result that the algorithm, referred to as ACIM, obtained by first augmenting the tree pattern using ICs, and then applying CIM, always finds the unique minimal equivalent query. While ACIM is polynomial time, it can be expensive in practice because of its inherent non-locality. We then present a fast algorithm, CDM, that identifies and eliminates local redundancies due to ICs, based on propagating ”information labels” up the tree pattern. CDM can be applied prior to ACIM for improving the minimization efficiency. We complement our analytical results with an experimental study that shows the effectiveness of our tree pattern minimization techniques.

Optimizing the secure evaluation of twig queries

The rapid emergence of XML as a standard for data exchange over the Web has led to considerable interest in the problem of securing XML documents. In this context, query evaluation engines need to ensure that user queries only use and return XML data the user is allowed to access. These added access control checks can considerably increase query evaluation time. In this paper, we consider the problem of optimizing the secure evaluation of XML twig queries. n nWe focus on the simple, but useful, multi-level access control model, where a security level can be either specified at an XML element, or inherited from its parent. For this model, secure query evaluation is possible by rewriting the query to use a recursive function that computes an elements security level. Based on security information in the DTD, we devise efficient algorithms that optimally determine when the recursive check can be eliminated, and when it can be simplified to just a local check on the elements attributes, without violating the access control policy. Finally, we experimentally evaluate the performance benefits of our techniques using a variety of XML data and queries.

Adaptive processing of top-k queries in XML

The ability to compute top-k matches to XML queries is gaining importance due to the increasing number of large XML repositories. The efficiency of top-k query evaluation relies on using scores to prune irrelevant answers as early as possible in the evaluation process. In this context, evaluating the same query plan for all answers might be too rigid because, at any time in the evaluation, answers have gone through the same number and sequence of operations, which limits the speed at which scores grow. Therefore, adaptive query processing that permits different plans for different partial matches and maximizes the best scores is more appropriate. In this paper, we propose an architecture and adaptive algorithms for efficiently computing top-k matches to XML queries. Our techniques can be used to evaluate both exact and approximate matches where approximation is defined by relaxing XPath axes. In order to compute the scores of query answers, we extend the traditional tf*idf measure to account for document structure. We conduct extensive experiments on a variety of benchmark data and queries, and demonstrate the usefulness of the adaptive approach for computing top-k queries in XML.

A comprehensive solution to the XML-to-relational mapping problem

The use of relational database management systems (RDBMSs) to store and query XML data has attracted considerable interest with a view to leveraging their powerful and reliable data management services. Due to the mismatch between the relational and XML data models, it is necessary to first shred and load the XML data into relational tables, and then btranslate XML queries over the original data into equivalent SQL queries over the mapped tables. Although there is a rich literature on XML-relational storage, none of the existing solutions addresses all the storage problems in a single framework. Works on mapping strategies often have little or no details about query translation, and proposals for query translation often target a specific mapping strategy. XML-storage solutions provided by RDBMS also have limitations. Notably, they are tied to a specific backend and use proprietary mapping languages, which not only may require a steep learning curve, but often are unable to express certain desirable mappings.n In order to address these limitations, we developed ShreX, a XML-to-relational mapping framework and system that provides the first comprehensive and end-to-end solution to the relational storage of XML data. Mappings in ShreX are defined through annotations to an XML Schema. The use of XML Schema simplifies the mapping process, since it does not require users to master a new specialized mapping language. The use of annotations allows mapping choices to be combined in many different ways. As a result, ShreX not only supports all the mapping strategies proposed in the literature, but also new useful strategies that had not been considered previously. ShreX provides generic (and automatic) document shredding and query translation capabilities; and it is portable --- its mapping specifications are independent of the database backend.

XML search: languages, INEX and scoring

The development of approaches to access XML content has generated a wealth of issues in information retrieval (IR) and database (DB) (e.g., [2, 15, 17, 20, 19, 47, 26, 32, 24]). While the IR community has traditionally focused on searching unstructured content, and has developed various techniques for ranking query results and evaluating their effectiveness, the DB community has focused on developing query languages and efficient evaluation algorithms for highly structured content. Recent trends in DB and IR research demonstrate a growing interest in merging IR and DB techniques for accessing XML content. Support for a combination of structured and full-text search for effectively querying XML documents was unanimous in a recent panel at SIGMOD 2005 [3], and is being widely studied in the IR community [20].

Report on the DB/IR panel at SIGMOD 2005

This paper summarizes the salient aspects of the SIGMOD 2005 panel on Databases and Information Retrieval: Rethinking the Great Divide. The goal of the panel was to discuss whether we should rethink data management systems architectures to truly merge Database (DB) and Information Retrieval (IR) technologies. The panel had very high attendance and generated lively discussions.