Identification of User Information Needs Based in the Analysis of Local Web Search Queries

Dokler, J. (2008). Identification of User Information Needs Based in the Analysis of Local Web Search Queries. Student dissertation for The Open University module M801 MSc in Software Development Research Dissertation.

Please note that this student dissertation is made available in the format that it was submitted for examination, thus the author has not been able to correct errors and/or departures from academic standards in areas such as referencing.



Together with the emergence of the World Wide Web some sixteen years ago there came the promise of instant feedback from users as to what information they want and when they want it. This information could then be used to determine the content and structure of web sites. As is usually the case, reality proved to be more complicated. Although user feedback was indeed instantaneous, the analysis was mostly limited to what people looked at as opposed to what they were looking for. Only in recent years has research focused on analysis of search queries that users submit to search engines. And search queries come close to representing what users are looking for. Still the majority of this research is based on queries from general purpose search engines. In this dissertation I explore the findings and ideas coming from the work on general search engines (and in parts on local search engines) and try to apply them in the context of a single web site to improve the structure and content of this web site. In particular I explore the idea that it is possible to determine the top level content elements of a web site from the analysis of the local search queries. Based on this I then proceed to explore the periodic change of web site’s content and how this information can be used to improve the web site. By implementing two different methods of search query analysis (manual and automatic clustering) and examining the results I show that search query analysis is a viable potential source of information about a web site’s structure and that identification of periodic changes of content can be used to amend a web site in advance before the next change occurs.

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