Ron Sacks-Davis's research while affiliated with RMIT University and other places

Text databases provide rapid access to collections of digital documents. Such databases have become ubiquitous: text search engines underlie the online text repositories accessible via the Web and are central to digital libraries and online corporate document management.

There has been a growing acceptance of the object-oriented data model as the basis of next generation database management systems (DBMSs). Both pure object-oriented DBMS (OODBMSs) and object-relational DBMS (ORDBMSs) have been developed based on object-oriented concepts. Object-relational DBMS, in particular, extend the SQL language by incorporating all the concepts of the object-oriented data model. A large number of products for both categories of DBMS is today available. In particular, all major vendors of relational DBMSs are turning their products into ORDBMSs [Nori, 1996].

Queries to text collections are resolved by ranking the documents in the collection and returning the highest-scoring documents to the user. An alternative retrieval method is to rank passages, that is, short fragments of documents, a strategy that can improve effectiveness and identify relevant material in documents that are too large for users to consider as a whole. However, ranking of passages can considerably increase retrieval costs. In this paper we explore alternative query evaluation techniques, and develop new techniques for evaluating queries on passages. We show experimentally that, appropriately implemented, effective passage retrieval is practical in limited memory on a desktop machine. Compared to passage ranking with adaptations of current document ranking algorithms, our new "DO-TOS" passage ranking algorithm requires only a fraction of the resources, at the cost of a small loss of effectiveness.

Ranking techniques are effective at finding answers in document collections but can be expensive to evaluate. We propose an evaluation technique that uses early recognition of which documents are likely to be highly ranked to reduce costs; for our test data, queries are evaluated in 2% of the memory of the standard implementation without degradation in retrieval effectiveness. cpu time and disk traffic can also be dramatically reduced by designing inverted indexes explicitly to support the technique. The principle of the index design is that inverted lists are sorted by decreasing within-document frequency rather than by document number, and this method experimentally reduces cpu time and disk traffic to around one third of the original requirement. We also show that frequency sorting can lead to a net reduction in index size, regardless of whether the index is compressed.

We propose a new scheme for managing files of variable-length dynamic records, based on storing the records in large, fixed-length blocks. We demonstrate the e#ectiveness of this scheme for text indexing, showing that it achieves space utilisation of over 95%. With an appropriate block size and caching strategy, our scheme requires on average around two disk accesses---one read and one write---for insertion of or change to a record.

Indexing and retrieval techniques for large text databases are well developed, but most of the techniques developed to date assume that the text to be indexed has little or no structure. With the growth in the use of sophisticated markup languages for text, a database system for structured documents should use, not just document content, but structural information and attributes, and should support queries on content, structure and attributes. In this paper we review and compare two recent approaches for accessing document collections. For one of the approaches, position-based indexing, queries are resolved by manipulating ranges of word o sets while for the other, based on a path model, the position of a word is represented in terms of the structural components that enclose it. The former allows slightly smaller indexes; the latter allows more efficient query evaluation.

We discuss a data model for the storage, retrieval and display of legislation in large database collections. Using free-text retrieval, the logical structure of SGML, and the browsing power of hypertext, arbitrary versions of statutes can be displayed, combining the power of traditional paper and current computer research tools.

Semi-structured data, including but not limited to structured documents, has speci#c characteristics and is used in ways di#erent to tabular data. SGML and XML are widely used to represent information of this type. The demands on systems that manage semi-structured data vary from those on traditional relational systems. This paper reviews the nature and characteristics of semi-structured data, and the functional needs of those applications, including query requirements, document description, manipulation, and document management needs. It examines alternative physical models for semi-structured data, and evaluates and compares alternative system architectures. 1

This paper describes the SIM architecture and the techniques used to support these standards. It describes how a standard based approach can be used to support structured queries and presents the techniques used by SIM for query evaluation

Introduction Provision of answers to informally phrased questions is a central part of information retrieval. These answers traditionally take the form of documents retrieved from a text database, but documents will often be unsatisfactory as answers. They may be large and unwieldy; the answer they represent may be diffuse, and therefore hard for the user to extract; and word-based retrieval systems may be misled by the breadth of vocabulary of a long document into believing it to be relevant. Indexing and returning parts of documents addresses these problems. We have approached the problem of partial documents in two ways. The first approach is to regard documents as an unstructured series of "pages" of text of similar length, each of which can be returned as an answer to a query. We would expect, under this approach, that any bias in the retrieval mechanism towards documents of a particular length should be eliminated. By regarding an answer to be the document from which an