Changeset 1205 for SMC4LRT/Outline.tex

Timestamp:

04/14/11 10:25:52 (13 years ago)

Author:

vronk

Message:

Expose intermediate (near finished) version

File:

• SMC4LRT/Outline.tex (modified) (3 diffs)

SMC4LRT/Outline.tex

@@ -207 +207 @@
 ontologies conceptualizing the linguistic domain
 
-They are special in that ("ontologized") Lexicons refere to them to describe linguistic properties of the Lexical Entries, as opposed to linking to Domain Ontologies to anchor Senses/Meanings.
+They are special in that ("ontologized") Lexicons refer to them to describe linguistic properties of the Lexical Entries, as opposed to linking to Domain Ontologies to anchor Senses/Meanings.
 Lexicalized Ontologies: LingInfo, lemon: LMF +  isocat/GOLD +  Domain Ontology
+
+a) as domain ontologies, describing aspects of the Resources\\
+b) as linguistic ontologies enriching the Lexicalization of Concepts
+
+Ontology and Lexicon \cite{Hirst2009}
+
+LingInfo/Lemon \cite{Buitelaar2009}
+
+We shouldn't need linguistic ontologies (LingInfo, LEmon), they are primarily relevant in the task of ontology population from texts, where the entities can be encountered in various word-forms in the context of the text.
+(Ontology Learning, Ontology-based Semantic Annotation of Text)
+And we are dealing with highly structured data with referenced in their nominal(?) form.
 
 Another special case are Controlled Vocabularies or Taxonomies/Classification Systems, let alone folksonomies, in that they identify terms and concepts/meanings, ie there is no explicit mapping between the language represenation and the concept, but rather the term is implicit carrier of the meaning/concept.
@@ -215 +226 @@
 controlled vocabularies?
 
-Ontology and Lexicon \cite{Hirst2009}
-
-LingInfo/Lemon \cite{Buitelaar2009}
 
 
@@ -353 +361 @@
 \end{itemize}
 
+A trivial example for a concept-based query expansion: 
+Confronted with a user query: \texttt{Actor.Name = Sue} and knowing that \texttt{Actor} is equivalent or similar to \texttt{Person} and \texttt{Name} is synonym to \texttt{FullName} the expanded query could look like:
+\texttt{Actor.Name = Sue OR Actor.FullName = Sue OR Person.Name =  Sue OR Person.FullName= is Sue}
+
+Another example concerning instance mapping: the user looking for all resource produced by or linked to a given institution, does not have to guess or care for various spellings of the name of the institution used in the description of the resources, but rather can browse through a controlled vocabulary of institutions and see all the resources of given institution. While this could be achieved by simple normalizing of the literal-values (and indeed that definitely has to be one processing step), the linking to an ontology, enables to user to also continue browsing the ontology to find institutions that are related to the original institution by means of being concerned with similar topics and retrieve a union of resources for such resulting cluster. Thus in general the user is enabled to work with the data based on information that is not present in the original dataset.
+
 \section{Semantic Mapping}