Fetch: A Personalised Information Retrieval Tool

Due to both the size and growth of the internet, new tools are needed to assist with the finding and extraction of very specific resources relevant to a user's task. Previously, the definition of relevance has been related to the matching between documents and query terms but recently the emphasis is shifting towards a more personalised model based on the relevance of a particular resource for one specific user. In this paper, we introduce our system, Fetch, which adopts this concept within an information-seeking environment specifically designed to provide users with means to describe a long-term multifaceted information need. By taking advantage of the way in which users bundle together groups of documents representing a particular topic, query languages as we know them can be taken to a higher and more useful level of abstraction. The agent personalises the search experience by using this information to formulate queries with the aim of returning documents relevant to the user's information need. In this paper we report on both qualitative and quantitative aspects of system use based on information collected in the pilot evaluation.