Knowledge Patterns for the Web: extraction, tranformation and reuse

Nuzzolese, Andrea Giovanni (2014) Knowledge Patterns for the Web: extraction, tranformation and reuse, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Informatica, 26 Ciclo. DOI 10.6092/unibo/amsdottorato/6562.
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Abstract

This thesis aims at investigating methods and software architectures for discovering what are the typical and frequently occurring structures used for organizing knowledge in the Web. We identify these structures as Knowledge Patterns (KPs). KP discovery needs to address two main research problems: the heterogeneity of sources, formats and semantics in the Web (i.e., the knowledge soup problem) and the difficulty to draw relevant boundary around data that allows to capture the meaningful knowledge with respect to a certain context (i.e., the knowledge boundary problem). Hence, we introduce two methods that provide different solutions to these two problems by tackling KP discovery from two different perspectives: (i) the transformation of KP-like artifacts to KPs formalized as OWL2 ontologies; (ii) the bottom-up extraction of KPs by analyzing how data are organized in Linked Data. The two methods address the knowledge soup and boundary problems in different ways. The first method provides a solution to the two aforementioned problems that is based on a purely syntactic transformation step of the original source to RDF followed by a refactoring step whose aim is to add semantics to RDF by select meaningful RDF triples. The second method allows to draw boundaries around RDF in Linked Data by analyzing type paths. A type path is a possible route through an RDF that takes into account the types associated to the nodes of a path. Then we present K~ore, a software architecture conceived to be the basis for developing KP discovery systems and designed according to two software architectural styles, i.e, the Component-based and REST. Finally we provide an example of reuse of KP based on Aemoo, an exploratory search tool which exploits KPs for performing entity summarization.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Nuzzolese, Andrea Giovanni
Supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze e ingegneria dell'informazione
Ciclo
26
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Knowledge Patterns, Semantic Web, Knowledge Extraction, Linked Data, Exploratory Search
URN:NBN
DOI
10.6092/unibo/amsdottorato/6562
Data di discussione
19 Maggio 2014
URI

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