Paper Info
Title
Web data reconciliation: models and experiences
Abstract
An increasing number of web sites offer structured information about recognizable concepts, relevant to many application domains, such as finance, sport, commercial products. However, web data is inherently imprecise and uncertain, and conflicting values can be provided by different web sources. Characterizing the uncertainty of web data represents an important issue and several models have been recently proposed in the literature. This chapter illustrates state-of-the-art Bayesan models to evaluate the quality of data extracted from the Web and reports the results of an extensive application of the models on real life web data. Experimental results show that for some applications even simple approaches can provide effective results, while sophisticated solutions are needed to obtain a more precise characterization of the uncertainty.
Year
DOI
Venue
2012
10.1007/978-3-642-34213-4_1
SeCO Book
Keywords
Field
DocType
application domain,conflicting value,real life web data,web data,extensive application,web site,web data reconciliation,effective result,commercial product,different web source
World Wide Web,Web intelligence,Computer science,Web engineering,Web modeling
Conference
Citations 
PageRank 
References 
2
0.38
17
Authors
4
Name
Order
Citations
PageRank
Lorenzo Blanco11098.68
Valter Crescenzi2105065.44
Paolo Merialdo31420195.45
Paolo Papotti483262.51