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Abstrakt
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.
Cytowania
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7
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0
Web of Science
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6
Scopus
Autorzy (6)
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Tarcisio Souza
- L3S Research Center and Leibniz Universität Hannover .
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Elena Demidova
- L3S Research Center and Leibniz Universität Hannover .
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Thomas Risse
- L3S Research Center and Leibniz Universität Hannover .
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Helge Holzmann
- L3S Research Center and Leibniz Universität Hannover .
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Gerhard Gossen
- L3S Research Center and Leibniz Universität Hannover .
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Informacje szczegółowe
- Kategoria:
- Aktywność konferencyjna
- Typ:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Tytuł wydania:
- W : Semantic Keyword-based Search on Structured Data Sources strony 153 - 166
- Język:
- angielski
- Rok wydania:
- 2015
- Opis bibliograficzny:
- Souza T., Demidova E., Risse T., Holzmann H., Gossen G., Szymański J.: Semantic URL Analytics to Support Efficient Annotation of Large Scale Web Archives// W : Semantic Keyword-based Search on Structured Data Sources/ : , 2015, s.153-166
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1007/978-3-319-27932-9_14
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 106 razy
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