Abstract
Since the Internet found its way into daily life, placing product information at the user’s disposal has become one of its most important tasks. As information sources are very heterogeneous concerning the provider as well as the structure, finding and consolidating the information for generating an all-embracing view on a product has become an important challenge. An auspicious approach for resolving the emerged problems are federated search techniques enriched with Information Extraction and Semantic Web concepts. We investigate possibilities for federated product search combining heterogeneous source types, i.e., structured and semi-structured sources from vendors, producers and third-party information providers. The developed approach is evaluated with a Ruby on Rails implementation.
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References
Fasli, M.: Shopbots: A Syntactic Present, A Semantic Future. IEEE Internet Computing 10(6), 69–75 (2006)
Kim, W., Choi, D., Park, S.: Intelligent Product Information Search Framework Based on the Semantic Web. In: 3rd ISWC, Hiroshima, Japan (2004)
Wolter, T., Schumacher, J., Matschi, M., et al.: Der shopinfo. XML-Standard. XML-Tage, Berlin (2006)
Hepp, M.: The True Complexity of Product Representation in the Semantic Web. In: 14th ECIS, Göteborg, Sweden (2006)
Wong, T., Lam, W., Wong, T.: An Unsupervised Framework for Extracting and Normalizing Product Attributes from Multiple Web Sites. In: 31st SIGIR, Singapore City (2008)
Lermann, K., Knoblock, C., Minton, S.: Automatic Data Extraction from Lists and Tables in Web Sources. In: IJCAI, Seattle, USA (2001)
Cheeseman, P., Stutz, J.: Bayesian Classification (AUTOCLASS): Theory and results. In: Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press, Cambridge (1996)
Carrasco, R., Oncina, J.: Learning Stochastic Regular Grammars by Means of a State Merging Method. In: Carrasco, R.C., Oncina, J. (eds.) ICGI 1994. LNCS, vol. 862. Springer, Heidelberg (1994)
Brunner, J., Ma, L., Wang, C., et al.: Explorations in the Use if Semantic Web Technologies for Product Information Management. In: WWW, Banff, Canada (2007)
Schuster, D., Walther, M., Braun, I.: Towards Federated Product Search From Heterogeneous Sources. In: WWW/Internet, Freiburg, Germany (2008)
Amazon: Associates Web Service (2008), http://www.amazon.com/E-Commerce-Service-AWS-home-page/b?ie=UTF8&node=12738641
Szinek, P.: scRUBYt! - A Simple to Learn and Use, yet Powerful Web Scraping Toolkit Written in Ruby (2008), http://scrubyt.org
Sulzberger, C.: The Levenshtein-Algorithm (2008), http://www.levenshtein.net
Banko, M., Cafarella, M., Soderland, S., et al.: Open Information Extraction from the Web. In: IJCAI, Hyderabad, India (2007)
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Walther, M., Schuster, D., Schill, A. (2009). Federated Product Search with Information Enrichment Using Heterogeneous Sources. In: Abramowicz, W. (eds) Business Information Systems. BIS 2009. Lecture Notes in Business Information Processing, vol 21. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01190-0_7
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DOI: https://doi.org/10.1007/978-3-642-01190-0_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01189-4
Online ISBN: 978-3-642-01190-0
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