Multi-Document Summaries of Swedish Documents as Search Result.
Carl-Oscar Erneholm · 2012
This thesis attempts to evaluate if it is viable for an information retrieval application to cluster the documents of a search result and generate multi-document summaries in query time, for Swedish documents. It evaluates the performance and quality of the document clustering algorithm k-means, and two multi-document summarization algorithms; one based on PageRank and the other based on the Cover Coefficient concept.The result shows that neither of the multi-document summarization algorithms is fast enough to run in query time, given a time limit of two seconds. But that they are both able to produce Swedish summaries of reasonably high quality. It further shows that k-means clusters documents quickly enough to be used in query time, but that the quality of the clusters are somewhat lacking and might not be good enough for practical use.