|Computer Lab Summarisation Demo|
Why generate webpages automatically?
In a research organisation such as ours, individual researchers take responsibility for maintaining their own webpages. In addition, researchers are organised into research groups, each of which maintains its own webpage. In this framework, information can get out of date. Most researchers keep their publications lists up-to-date. However, research summaries and the like are updated less often, on individual researcher homepages and on group homepages. Thus reading research profiles does not always give an accurate overview of what is currently being worked on.
Further, the tree structure (lab > research groups > researchers) make browsing difficult. As each researcher's webpage is maintained indivdually, links between researchers are often not obvious. A surfer then needs to repeatedly move up and down the tree hierarchy to browse the profiles of different researchers.
In these automatically generated pages, content is extracted from publication titles, and hence stays up-to-date. Information is formatted in a way that facilitates browsing. The left of the screen contains links to researchers of the same group and the middle contains a research profile. In addition, the right of the screen contains a list of recommendations: other researchers with similar research interests. This allows for browsing the website as a graph, without having to repeatedly move up and down the tree hierarchy.
How these webpages are generatedThe program starts with a list of publications extracted from individual researchers' webpages; for example:
Individual researcher pagesTo create a webpage for an individual researcher, the key-phrases from all the paper titles authored by that researcher are clustered together - an example cluster is shown below:
A representative phrase is selected from each cluster ('information retrieval' from the cluster above) and this phrase is associated with all the publication dates of papers the terms in the cluster come from . These extracted key-phrases are eumerated as lists in five year intervals; for example:
Recommendations (related people)Recommendations for related people are generated by comparing the terms extracted between 2000 and 2008 for each researcher. The seven most similar researchers are shown in tabular form along with a list of terms from those researchers' profiles that are relevant to the researcher being viewed; eg:
Research Group PagesGroup pages are produced by summarising the pages of researchers in the group. Terms are clustered according to who is working on them. The group page is presented as a list of clusters. This presentation highlights how group members collaborate with each other, and for each term shows the relevant researchers, making navigation easier; for example: