Alan Dix - research topics


Query-by-Browsing (QbB) is a novel database interface designed to explore issues of human interaction with intelligent systems. Standard "Query-by-Example" is not really by example at all. The user has to construct a template of the query. In contrast QbB really is "by example". The user selects records of interest from a list of records and machine learning algorithms generate a query which matches the records selected. This query is used to extend the selection and is reflected back to the user either as a textual query (e.g. SQL) or as a QBE style query. The challenges from a research perspective include the choice of algorithms (machine learning, traditional AI, genetic algorithms, neural networks) and handling the interaction. There are typically many queries which explain a given set of selected records. The algorithm must choose one which seems sensible to the user. However good the algorithm, it will not guess right every time and so the deign of the system must allow the user to interact with the intelligent agent in a graceful manner.

Try it out the new online version - Query-by-Browsing on the Web

If you have a Macintosh you can also download a demonstration program

Some publications featuring Query-by-Browsing

maintained by Alan Dix