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Visual support for ontology learning: an experience report
Ontology learning methods aim to automate ontology
construction. They are complex methods involving several
elements such as documents, terms and concepts. During the development of an ontology learning method, as well as during its deployment, several situations occur where
understanding the relations between these elements is crucial. Our hypothesis is that visual techniques can be used to aid this understanding. To support this claim, we present a set of such complex situations and describe the visual solutions that we developed to support them
A Survey of Paraphrasing and Textual Entailment Methods
Paraphrasing methods recognize, generate, or extract phrases, sentences, or
longer natural language expressions that convey almost the same information.
Textual entailment methods, on the other hand, recognize, generate, or extract
pairs of natural language expressions, such that a human who reads (and trusts)
the first element of a pair would most likely infer that the other element is
also true. Paraphrasing can be seen as bidirectional textual entailment and
methods from the two areas are often similar. Both kinds of methods are useful,
at least in principle, in a wide range of natural language processing
applications, including question answering, summarization, text generation, and
machine translation. We summarize key ideas from the two areas by considering
in turn recognition, generation, and extraction methods, also pointing to
prominent articles and resources.Comment: Technical Report, Natural Language Processing Group, Department of
Informatics, Athens University of Economics and Business, Greece, 201
Optical tomography: Image improvement using mixed projection of parallel and fan beam modes
Mixed parallel and fan beam projection is a technique used to increase the quality images. This research focuses on enhancing the image quality in optical tomography. Image quality can be deļ¬ned by measuring the Peak Signal to Noise Ratio (PSNR) and Normalized Mean Square Error (NMSE) parameters. The ļ¬ndings of this research prove that by combining parallel and fan beam projection, the image quality can be increased by more than 10%in terms of its PSNR value and more than 100% in terms of its NMSE value compared to a single parallel beam
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