Programme booklet (pdf)

54
CLIN 21 – CONFERENCE PROGRAMME
Personalized Knowledge Discovery: Combining Social
Media and Domain Ontologies
Abstract
Markus, Thomas and Westerhout, Eline and Monachesi, Paola
Utrecht University
We present a system that facilitates knowledge discovery by means of structured
domain ontologies. The user can discover new concepts and relations by exploring an
expert approved ontological structure which has been automatically enriched with new
concepts, relations and lexicalisations originating from social media. The system also
on-the-fly interlinks the conceptual knowledge in the ontology with noisy data coming
from social media on the conceptual level.
Our ontology enrichment methodology identifies salient terms using similarity
measures and determines the appropriate word senses for each term by employing a
disambiguation algorithm. The appropriate relation between the new concept (word
sense) and the existing ones is either extracted from DBpedia or from text documents
retrieved from the web. The disambiguation algorithm is also used to store the original
context of each term, that is, the term itself, its meaning, associated person and
resource. These personalised contexts are stored using the MOAT semantic vocabulary.
The enriched ontology and the disambiguation methodology allow us to give a
personalised semantic interpretation to each search result in the context of the
enriched domain ontology and the user. The amount of conceptual overlap between a
document and the person using the system is employed to offer personalised
recommendation of documents.
The advantages that this approach brings to students has been evaluated as part of a
university course with a large group of students and a separate control group.
Corresponding author: Thomas.Markus@phil.uu.nl