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136 lines
6.2 KiB
TeX
136 lines
6.2 KiB
TeX
\chapter{Web reasoning}
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\section{Semantic web}
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\begin{description}
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\item[Semantic web] \marginnote{Semantic web}
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Method to represent and reason on the data available on the web.
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Semantic web aims to preserve the characteristics of the web, this includes:
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\begin{itemize}
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\item Globality.
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\item Information distribution.
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\item Information inconsistency of contents and links (as everyone can publish).
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\item Information incompleteness of contents and links.
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\end{itemize}
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Information is structured using ontologies and logic is used as inference mechanism.
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New knowledge can be derived through proofs.
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\item[Uniform resource identifier] \marginnote{URI}
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Naming system to uniquely identify concepts.
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Each URI corresponds to one and only one concept, but multiple URIs can refer to the same concept.
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\item[XML] \marginnote{XML}
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Markup language to represent hierarchically structured data.
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An XML can contain in its preamble the description of the grammar used within the document.
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\item[Resource description framework (RDF)] \marginnote{Resource description framework (RDF)}
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XML-based language to represent knowledge.
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Based on triplets:
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\begin{center}
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\texttt{<subject, predicate, object>}\\
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\texttt{<resource, attribute, value>}
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\end{center}
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RDF supports:
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\begin{descriptionlist}
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\item[Types] Using the attribute \texttt{type} which can assume an URI as value.
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\item[Collections] Subjects and objects can be bags, sequences or alternatives.
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\item[Meta-sentences] Reification of the sentences (e.g. "X says that Y\dots").
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\end{descriptionlist}
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\begin{description}
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\item[RDF schema] \marginnote{RDF schema}
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RDF can be used to describe classes and relations with other classes (e.g. \texttt{type}, \texttt{subClassOf}, \texttt{subPropertyOf}, \dots)
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\item[Representation] \phantom{}
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\begin{descriptionlist}
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\item[Graph] A graph where nodes are subjects or objects and edges are predicates.
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\begin{example} \phantom{}
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\begin{center}
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\includegraphics[width=0.4\textwidth]{img/rdf_graph_example.png}
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\end{center}
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The graph stands for:
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\texttt{http://www.example.org/index.html} has a \texttt{creator} with staff id \texttt{85740}.
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\end{example}
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\item[XML]
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\begin{example} \phantom{}
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\begin{lstlisting}[mathescape=true, language=xml]
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<rdf:RDF
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xmlns:rdf=http://www.w3.org/1999/02/22-rdf-syntax-ns#
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xmlns:contact=http://www.w3.org/2000/10/swap/pim/contact#>
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<contact:Person rdf:about="http://www.w3.org/People/EM/contact#me">
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<contact:fullName>Eric Miller</contact:fullName>
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<contact:mailbox rdf:resource="mailto:em@w3.org"/>
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<contact:personalTitle>Dr.</contact:personalTitle>
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</contact:Person>
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</rdf:RDF>
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\end{lstlisting}
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\end{example}
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\end{descriptionlist}
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\item[Database similarities]
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RDF aims to integrate different databases:
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\begin{itemize}
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\item A DB record is an RDF node.
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\item The name of a column can be seen as a property type.
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\item The value of a field corresponds to the value of a property.
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\end{itemize}
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\end{description}
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\item[RDFa] \marginnote{RDFa}
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Specification to integrate XHTML and RDF.
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\item[SPARQL] \marginnote{SPARQL}
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Language to query different data sources that support RDF (natively or through a middleware).
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\item[Ontology web language (OWL)] \marginnote{Ontology web language (OWL)}
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Ontology-based on RDF and description logic fragments.
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Three levels of expressivity are available:
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\begin{itemize}
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\item OWL lite.
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\item OWL DL.
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\item OWL full.
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\end{itemize}
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An OWL has:
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\begin{descriptionlist}
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\item[Classes] Categories.
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\item[Properties] Roles and relations.
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\item[Instances] Individuals.
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\end{descriptionlist}
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\end{description}
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\section{Knowledge graphs}
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\begin{description}
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\item[Knowledge graph] \marginnote{Knowledge graph}
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Knowledge graphs overcome the computational complexity of T-box reasoning with semantic web and description logics.
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\begin{itemize}
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\item Use a simple vocabulary with a simple but robust corpus of types and properties adopted as a standard.
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\item Represent a graph with terms as nodes and edges connecting them.
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Knowledge is therefore represented as triplets \texttt{(h, r, t)} where \texttt{h} and \texttt{t} are entities and \texttt{r} is a relation.
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\item Logic formulas are removed. T-box and A-box can be seen as the same concept. There is no reasoning but only facts.
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\item Data does not have a conceptual schema and can come from different sources with different semantics.
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\item Graph algorithms to traverse the graph and solve queries.
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\end{itemize}
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\item[KG quality] \marginnote{Quality}
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\begin{description}
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\item[Coverage] If the graph has all the required information.
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\item[Correctness] If the information is correct (can be objective or subjective).
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\item[Freshness] If the content is up-to-date.
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\end{description}
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\item[Graph embedding] \marginnote{Graph embedding}
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Project entities and relations into a vectorial space for ML applications.
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\begin{description}
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\item[Link prediction] Given two entities \texttt{h} and \texttt{t}, determine the relation \texttt{r} between them.
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\item[Entity prediction] Given an entity \texttt{h} and a relation \texttt{t}, determine an entity \texttt{t}-related to \texttt{h}.
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\end{description}
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\end{description} |