12,472 research outputs found
Evaluating the semantic web: a task-based approach
The increased availability of online knowledge has led to the design of several algorithms that solve a variety of tasks by harvesting the Semantic Web, i.e. by dynamically selecting and exploring a multitude of online ontologies. Our hypothesis is that the performance of such novel algorithms implicity provides an insight into the quality of the used ontologies and thus opens the way to a task-based evaluation of the Semantic Web. We have investigated this hypothesis by studying the lessons learnt about online ontologies when used to solve three tasks: ontology matching, folksonomy enrichment, and word sense disambiguation. Our analysis leads to a suit of conclusions about the status of the Semantic Web, which highlight a number of strengths and weaknesses of the semantic information available online and complement the findings of other analysis of the Semantic Web landscape
Comparing human and automatic thesaurus mapping approaches in the agricultural domain
Knowledge organization systems (KOS), like thesauri and other controlled
vocabularies, are used to provide subject access to information systems across
the web. Due to the heterogeneity of these systems, mapping between
vocabularies becomes crucial for retrieving relevant information. However,
mapping thesauri is a laborious task, and thus big efforts are being made to
automate the mapping process. This paper examines two mapping approaches
involving the agricultural thesaurus AGROVOC, one machine-created and one human
created. We are addressing the basic question "What are the pros and cons of
human and automatic mapping and how can they complement each other?" By
pointing out the difficulties in specific cases or groups of cases and grouping
the sample into simple and difficult types of mappings, we show the limitations
of current automatic methods and come up with some basic recommendations on
what approach to use when.Comment: 10 pages, Int'l Conf. on Dublin Core and Metadata Applications 200
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