Semantic URL Analytics to Support Efficient Annotation of Large Scale Web Archives
Long-term Web archives comprise Web documents gathered over longer time periods and can easily reach hundreds of terabytes in size. Semantic annotations such as named entities can facilitate intelligent access to the Web archive data. However, the annotat
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L3S Research Center and Leibniz Universit¨ at Hannover, Hannover, Germany {Souza,Demidova,Risse,Holzmann,Gossen}@L3S.de 2 Gdansk University of Technology, Gda´ nsk, Poland [email protected]
Abstract. Long-term Web archives comprise Web documents gathered over longer time periods and can easily reach hundreds of terabytes in size. Semantic annotations such as named entities can facilitate intelligent access to the Web archive data. However, the annotation of the entire archive content on this scale is often infeasible. The most efficient way to access the documents within Web archives is provided through their URLs, which are typically stored in dedicated index files. The URLs of the archived Web documents can contain semantic information and can offer an efficient way to obtain initial semantic annotations for the archived documents. In this paper, we analyse the applicability of semantic analysis techniques such as named entity extraction to the URLs in a Web archive. We evaluate the precision of the named entity extraction from the URLs in the Popular German Web dataset and analyse the proportion of the archived URLs from 1,444 popular domains in the time interval from 2000 to 2012 to which these techniques are applicable. Our results demonstrate that named entity recognition can be successfully applied to a large number of URLs in our Web archive and provide a good starting point to efficiently annotate large scale collections of Web documents.
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Introduction and Motivation
Web archives are a unique source of data reflecting rapid evolution of the digital world. Recently, an increasing interest in using the data stored within the Web archives for research purposes has been observed in several disciplines such as history or digital sociology [14]. For example, as discussed in [6], Web archives can be an important source for communication and media history and within historiography in general. Unfortunately, existing Web archives are very difficult to use since most often only a URL based access is provided. Researchers are typically interested in a few relevant Web sites regarding a given topic, domain or time frame to be selected for manual analysis. Finding such relevant data for a specific purpose within the Web archive is still very challenging. This is mainly attributed to the very large c Springer International Publishing Switzerland 2015 J. Cardoso et al. (Eds.): KEYWORD 2015, LNCS 9398, pp. 153–166, 2015. DOI: 10.1007/978-3-319-27932-9 14
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size of the data coupled with the lack of efficient tools for annotation, search and exploration. Indexing existing Web archives, which often contain hundreds of terabytes of data, is difficult and hence, full-text search capabilities are rarely available, not to mention more sophisticated semantic content analytics. In this context, we look at different ways to obtain relevant documents from a Web archive efficiently and analyse the role of URLs of the archived documents towards this goal. The advantage of using URLs is twofold: First, the URLs of
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