Search

In the context of e-government and more specifically that of parliament, this paper tackles the problem of finding Members of Parliament (MPs) according to their profiles which have been built from their speeches in plenary or committee sessions. The paper presents a common solution for two problems: firstly, a member of the public who is concerned about a certain issue might want to know who the best MP is for dealing with their problem (recommending task); and secondly, each new piece of textual information that reaches the house must be correctly allocated to the appropriate MP according to its content (filtering task). This paper explores both these ways of searching for relevant people conceptually by encapsulating them into a single problem: that of searching for the relevant MP’s profile given an information need. Our research work proposes various profile construction methods (by selecting and weighting appropriate terms) and compares these using different retrieval models to evaluate their quality and suitability for different types of information needs in order to simulate real and common situations. [ABSTRACT FROM AUTHOR]

The authors propose improved ways of analysing web server log files. Traditionally web site statistics focus on giving a big (and shallow) picture analysis based on all transaction log entries. The pictures are, however, distorted because of the problems associated with resolving Internet protocol (IP) numbers to a single user and cross-border IP registration. The authors argue that analysing extracted sub-groups and categories presents a more accurate picture of the data and that the analysis of the online behaviour of selected individuals (rather than of very large groups) can add much to our understanding of how people use web sites and, indeed, any digital information source. The analysis is labelled `micro' to distinguish it from traditional macro, big picture transactional log analysis. The methods are illustrated with recourse to the logs of the Surgery Door (www.surgerydoor.co.uk) consumer health web site. It was found that use attributed to academic users gave a better approximation of the sites' geographical distribution of users than an analysis based on all users. This occurs as academic institutions, unlike other user types, register in their host country. Selecting log entries where each user is allocated a unique IP number can be particularly beneficial, especially to analyses of returnees. Finally the paper tracks the online behaviour of a small number of IP numbers, in an example of the application of microanalysis, [ABSTRACT FROM PUBLISHER]