Machine acts: capturing context for personal search

The development of new digital media (picture, video and audio technologies), cheap storage devices on personal computers, and the introduction of the Internet, have resulted in a significant rise in the amount of information which users can search in order to answer specific questions of interest. This large increase in the availability of information has not been matched by corresponding improvements in searching strategies for locating and identifying relevant information. Whilst users access the Internet to find new information they also frequently use it to locate information which has been useful to them in the past. This is also true on personal computers, where the majority of searches are concerned with re-finding existing information. Traditional Information Retrieval and Internet search technologies return a large number of results, many of which are not relevant. These query techniques utilize keywords (often in the form of Regular Expressions) and Boolean expressions to answer user requests. The queries are simply not expressive enough. This thesis proposes a new search strategy, which depends upon the use of contextual information when formulating queries. [Continues.]