Modern search engines answer keyword-based queries extremely efficiently. The impressive speed is due to clever inverted index structures, caching, a domain-independent knowledge of strings, and thousands of machines. Several research efforts have attempted to generalize keyword search to keytree and keygraph searching, because trees and graphs have many applications in next-generation database systems. This paper surveys both algorithms and applications, giving some emphasis to our own work.

In query-intensive database application areas, like decision support and data mining, systems that use vertical fragmentation have a significant performance advantage. In order to support relational or object oriented applications on top of such a fragmented data model, a flexible yet powerful intermediate language is needed. This problem has been successfully tackled in Monet, a modern extensible database kernel developed by our group. We focus on the design choices made in the Monet Interpreter Language (MIL), its algebraic query language, and outline how its concept of tactical optimization enhances and simplifies the optimization of complex queries. Finally, we summarize the experience gained in Monet by creating a highly efficient implementation of MIL.

The explosion in complex multi-media content makes it crucial for database systems to support such data efficiently. We make the case that the next generation of object-relational database Data Type (E-ADT) technology, rather than on the “blackbox ” ADTs used in current systems. An E-ADT is an abstract data type that exposes the semantics of its methods. Query optimizations are performed using these semantics, resulting in efficient query processing. The added functionality does not compromise the modularity of data types and the extensibility of the type system. Fundamental architectural changes are required to build such a database system; these have been explored through the implementation of E-ADTs in Predutor. Initial performance results demonstrate an order of magnitude in performance improvements. 1

A knowledge-based approach to retrieve medical images by feature and content with spatial and temporal constructs is developed. Selected objects of interest in a medical image (e.g. x-ray, MR image) are segmented, and contours are generated from these objects. Features (e.g. shape, size, texture) and content (e.g. spatial relationships among objects) are extracted and stored in a feature and content database. Knowledge about image features can be expressed as a hierarchical structure called a Type Abstraction Hierarchy (TAH). The high-level nodes in the TAH represent more general concepts than low-level nodes. Thus, traversing along TAH nodes allows approximate matching by feature and content if an exact match is not available. TAHs can be generated automatically by clustering algorithms based on feature values in the databases and hence are scalable to large collections of image features. Further, since TAHs are generated based on user classes and applications, they are context- and u...

An unordered labeled tree is a tree in which each node has a string label and the parent-child relationship is significant, but the order among siblings is unimportant. This paper presents an approach...

Traditional databases store sets of relatively static records with no pre-defined notion of time, unless timestamp attributes are explicitly added. While this model adequately represents commercial catalogues or repositories of personal information, many current and emerging applications require support for on-line analysis of rapidly changing data streams. Limitations of traditional DBMSs in supporting streaming applications have been recognized, prompting research to augment existing technologies and build new systems to manage streaming data. The purpose of this paper is to review recent work in data stream management systems, with an emphasis on data models, continuous query languages, and query evaluation and optimization techniques. We also give examples of streaming queries in various applications and review related work in modeling lists and sequences. 1

In this paper we pursue the study of Alignment Calculus, a declarative string database query language that supports both string querying and restructuring. This language is aimed for applications such as molecular biology databases, where the basic data type is a string, and the queries are combinatorial in nature. The declarative nature of our language does, however, require some additional effort in its implementation. Here we solve this problem by first defining a domain independent syntactic subset of the full language and then developing a query evaluation mechanism for this sublanguage. This mechanism then handles the required restructuring operations in a finite manner.

Types and Inheritance : : : : : : : : : : : : : : : : : : : : : : : : : : 39 5.2.3 Modeling DTD Constraints : : : : : : : : : : : : : : : : : : : : : : : : : : : : 41 5.2.4 Performance Issues : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 43 6 Related Work 45 6.1 Database Models for Structured Documents : : : : : : : : : : : : : : : : : : : : : : : 45 6.2 Other Multimedia Databases : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 49 6.2.1 Presentation-Oriented Multimedia Databases : : : : : : : : : : : : : : : : : : 49 6.2.2 Miscellaneous Multimedia Databases : : : : : : : : : : : : : : : : : : : : : : : 50 7 Conclusions and Future Work 51 Bibliography 53 A DTD for Multimedia News Articles 57 B Type Declarations 60 B.1 Atomic Types : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 60 B.2 Top-Level Element Hierarchy : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 63 B.3 Type ArticleRoot : : : : : : : : : : :...

I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii Database management systems (DBMSs) have been used successfully in traditional business applications that require persistent data storage and an efficient querying mechanism. Typically, it is assumed that the data are static, unless explicitly modified or deleted by a user or application. Database queries are executed when issued and their answers reflect the current state of the data. However, emerging applications, such as sensor networks, real-time Internet traffic analysis, and on-line financial trading, require support for processing of unbounded data streams. The fundamental assumption of a data stream management system (DSMS) is that new data are generated continually, making it infeasible to store a stream in its entirety. At best, a sliding window of recently arrived data may be maintained, meaning that old data must be removed as time goes on. Furthermore, as the contents of the sliding windows evolve over time, it makes

One of the challenges facing today's database systems is the need to support complex data types, which are of growing importance in new application areas. The thesis addresses this problem, with a specific focus on supporting sequence data. A large part of the thesis deals with the details of sequences. Issues covered include the model for sequence data, an algebra of operators to query the data, a query language to express the queries, optimization techniques and query processing algorithms. Performance results are presented from an implementation of these ideas, demonstrating the effects of the various optimizations. This detailed exploration of sequence data is one contribution of the thesis. The second contribution is a solution to the problem of integrating different data types, including sequences and relations, in a general-purpose database system. The thesis discusses the drawbacks of existing solutions, and then proposes a solution based on a novel E-ADT paradigm. This parad...