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This paper presents a systematic XML Schema design approach which conceptually captures semantics of the problem domain at conceptual level and represents such semantics in XML Schema at schema level. At the conceptual level, objects, their inter‐relationships and constraints are semantically powered by object‐oriented models. At the schema level, these conceptual semantics are comprehensively represented in textbased representation of XML Schema using various schema components and design styles, each of which offers different quality characteristics. Two primary design styles in use are nesting and linking. The nesting design styles are developed based on the choice of schema components and their definition/declaration scopes (global vs. local), whereas the linking design styles use referencing facilities provided by XML Schema and other XML technologies such as XLink and XPointer. With an in‐depth analysis of outstanding problems of existing approaches, the proposed design approach is motivated to help improve the quality and robustness of the XML documents in large‐scale XML‐based applications.

This paper presents a framework which combines data and text retrieval techniques to exercise and evaluate ontology based query expansions. We prepare by using linguistic techniques to identify query and document concepts, locating them in a ontologically defined semantic space. Expansions originate from the identified query concepts, with success determined by matching in the relevant document set. We identify three orthogonal dimensions that can affect query expansion success; relationship source, success measure technique, and query expansion technique. Expansion technique is further divided into six different categories: simple pruning, complex probability, voting, directional, semantic propagation, and multiple source concept. We describe each technique and show examples where they would be useful. The system architecture used facilitates plugging in of various expansion and evaluation routines, and flowing results from one method to the next. The system is useful for microanalysis of query expansion, discovering which components of ontological derived knowledge most influence query expansion success. In this work, we apply our framework to the medical domain.

Despite the increasing demand for an effective XML document repository, many are still reluctant to store XML documents in their natural tree form. One main reason is the inadequacy of XML query languages to update the tree‐form XML documents. Even though some of the languages have supported minimum update facilities, they do not concern on preserving the documents constraints. The results are updated documents with very low database integrity. In this paper, we propose a methodology to accommodate XML Update without violating the conceptual constraints of the documents. The method takes form as a set of functions that perform checking mechanisms before update operations. In this paper we discuss the conceptual constraints embedded in three different relationship structures: association, aggregation and inheritance relationship. We highlight four constraints related with association relationship (nuber of participants, referential integrity, cardinality, and adhesion), five constraints related with aggregation relationship (cardinality, adhesion, ordering, homogeneity and share‐ability) and two constraints related to inheritance relationship (disjoint and number of super‐class). In addition, a specific constraint, which is collection type of children, will also be discussed. The proposed method can be implemented in different ways, for example in this paper we use XQuery language. Since the XML update requires schema, in this paper we also propose the mapping of the these constraints in the conceptual level to the XML Schema. We use XML Schema for structure validation, even though the algorithm can be used by any schema languages.

Semi‐structured data are commonly represented by labeled flat db‐graphs. In this paper, we study an extension of db‐graph model for representing nested semi‐structured data. This extension allows one to have db‐graphs whose vertex labels are db‐graphs themselves. Bringing the data model closer to the natural presentation of data stored via Web documents is the main motivation behind nesting db‐graphs. The importance of nested db‐graphs is similar to the importance of nested tables in relational model. The main purpose of the paper is to provide a mechanism to query nested semi‐structured data and Web forms in a uniform way. Most of the languages proposed so far have been designed as extensions of SQL with, among others, the advantage to provide a user‐friendly syntax and commercial flavor. The major focus of the paper is on defining a graph query language in a multi‐sorted calculus like style.