Abstract
This research is directed towards automating the Web Site summarization task. To achieve this objective, an approach, which applies machine learning and natural language processing techniques, is employed. The automatically generated summaries are compared to manually constructed summaries from DMOZ Open Directory Project. The comparison is performed via a formal evaluation process involving human subjects. Statistical evaluation of the results demonstrates that the automatically generated summaries are as informative as human authored DMOZ summaries and significantly more informative than home page browsing or time limited site browsing.
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Zhang, Y.Z., Zincir-Heywood, N., Milios, E. (2003). Summarizing Web Sites Automatically. In: Xiang, Y., Chaib-draa, B. (eds) Advances in Artificial Intelligence. Canadian AI 2003. Lecture Notes in Computer Science, vol 2671. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44886-1_22
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DOI: https://doi.org/10.1007/3-540-44886-1_22
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