The ARCOMEM Architecture for Social- and Semantic-Driven Web Archiving

Future Internet

Thomas Risse³  Elena Demidova³  Stefan Dietze³  Wim Peters⁶  Nikolaos Papailiou⁴  Katerina Doka⁴  Yannis Stavrakas⁴  Vassilis Plachouras⁴  Pierre Senellart¹  Florent Carpentier⁵  Amin Mantrach²  Bogdan Cautis¹  Patrick Siehndel³  Dimitris Spiliotopoulos⁷ 

[1]CNRS LTCIT, Institut Mines-Télécom, Télécom ParisTech, 75634 Paris Cedex 13, France

[2] E-Mails:

[3]Yahoo Research, 08018 Barcelona, Spain

[4] E-Mail:

[5]L3S Research Center, Leibniz Universität Hannover, Hannover 30167, Germany

[6] E-Mails:

[7]ATHENA - Research and Innovation Center in Information, Communication and Knowledge Technologies, 15125 Maroussi, Athens, Greece

[8] E-Mails:

[9]Internet Memory Foundation, 45 ter rue de la Révolution, 93100 Montreuil, France

[10] E-Mail:

[11]NLP Group, Department of Computer Science, University of Sheffield, S1 4DP Sheffield, UK

[12] E-Mail:

[13]Athens Technology Center (ATC), 15233 Halandri Athens, Greece

[14] E-Mail:

关键词: web archiving;    web crawler;    architecture;    text analysis;    social Web;   

DOI  :  10.3390/fi6040688

来源: mdpi

【 摘 要 】

The constantly growing amount of Web content and the success of the Social Web lead to increasing needs for Web archiving. These needs go beyond the pure preservation of Web pages. Web archives are turning into “community memories” that aim at building a better understanding of the public view on, e.g., celebrities, court decisions and other events. Due to the size of the Web, the traditional “collect-all” strategy is in many cases not the best method to build Web archives. In this paper, we present the ARCOMEM (From Collect-All Archives to Community Memories) architecture and implementation that uses semantic information, such as entities, topics and events, complemented with information from the Social Web to guide a novel Web crawler. The resulting archives are automatically enriched with semantic meta-information to ease the access and allow retrieval based on conditions that involve high-level concepts.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.