On Region Algebras, XML Databases, and Information Retrieval

This paper describes some new ideas on developing a logical algebra for databases that manage textual data and support information retrieval functionality. We describe a first prototype of such a system

A Database Approach to Content-based XML retrieval

This paper describes a rst prototype system for content-based retrieval from XML data. The system's design supports both XPath queries and complex information retrieval queries based on a language modelling approach to information retrieval. Evaluation using the INEX benchmark shows that it is beneficial if the system is biased to retrieve large XML fragments over small fragments

Analyzing Fuzzy Logic Computations with Fuzzy XPath

Implemented with a fuzzy logic language by using the FLOPER tool developed in our research group, we have recently designed a fuzzy dialect of the popular XPath language for the flexible manipulation of XML documents. In this paper we focus on the ability of Fuzzy XPath for exploring derivation trees generated by FLOPER once they are exported in XML format, which somehow serves as a debugging/analizing tool for discovering the set of fuzzy computed answers for a given goal, performing depth/breadth-first traversals of its associated derivation tree, finding non fully evaluated branches, etc., thus reinforcing the bi-lateral synergies between Fuzzy XPath and FLOPER

Expression and Efficient Processing of Fuzzy Queries in a Graph Database Context

International audienceGraph databases have aroused a large interest in the last years thanks to their large scope of potential applications (e.g. social networks, biomedical networks, data stemming from the web). In a similar way as what has already been proposed in relational databases, defining a language allowing a flexible querying of graph databases may greatly improve usability of data. This paper focuses on the notion of fuzzy graph database and describes a fuzzy query language that makes it possible to handle such database, which may be fuzzy or not, in a flexible way. This language, called FUDGE, can be used to express preference queries on fuzzy graph databases. The preferences concern i) the content of the vertices of the graph and ii) the structure of the graph. The FUDGE language is implemented in a system, called SUGAR, that we present in this article. We also discuss implementation issues of the FUDGE language in SUGAR

Intuitionistic fuzzy XML query matching and rewriting

With the emergence of XML as a standard for data representation, particularly on the web, the need for intelligent query languages that can operate on XML documents with structural heterogeneity has recently gained a lot of popularity. Traditional Information Retrieval and Database approaches have limitations when dealing with such scenarios. Therefore, fuzzy (flexible) approaches have become the predominant. In this thesis, we propose a new approach for approximate XML query matching and rewriting which aims at achieving soft matching of XML queries with XML data sources following different schemas. Unlike traditional querying approaches, which require exact matching, the proposed approach makes use of Intuitionistic Fuzzy Trees to achieve approximate (soft) query matching. Through this new approach, not only the exact answer of a query, but also approximate answers are retrieved. Furthermore, partial results can be obtained from multiple data sources and merged together to produce a single answer to a query. The proposed approach introduced a new tree similarity measure that considers the minimum and maximum degrees of similarity/inclusion of trees that are based on arc matching. New techniques for soft node and arc matching were presented for matching queries against data sources with highly varied structures. A prototype was developed to test the proposed ideas and it proved the ability to achieve approximate matching for pattern queries with a number of XML schemas and rewrite the original query so that it obtain results from the underlying data sources. This has been achieved through several novel algorithms which were tested and proved efficiency and low CPU/Memory cost even for big number of data sources

A GPFCSP-Based Fuzzy XQuery Interpreter

Nowadays XQuery has become the strongest standard for querying XML data. However, most of the real world information is in the form of imprecise, vague, ambiguous, uncertain and incomplete values. That is why there is a need for a flexible query language in which users can formulate queries that arise from their own criteria. In this paper, we propose an implementation of the Fuzzy XQuery - an extension of the XQuery query language based on the fuzzy set theory. In particular, we provide priority, threshold and fuzzy expressions for handling flexible queries. In addition, we have implemented an interpreter for this language by using the GPFCSP concept in Java and eXist-db environment

A survey on tree matching and XML retrieval

International audienceWith the increasing number of available XML documents, numerous approaches for retrieval have been proposed in the literature. They usually use the tree representation of documents and queries to process them, whether in an implicit or explicit way. Although retrieving XML documents can be considered as a tree matching problem between the query tree and the document trees, only a few approaches take advantage of the algorithms and methods proposed by the graph theory. In this paper, we aim at studying the theoretical approaches proposed in the literature for tree matching and at seeing how these approaches have been adapted to XML querying and retrieval, from both an exact and an approximate matching perspective. This study will allow us to highlight theoretical aspects of graph theory that have not been yet explored in XML retrieval