Marco Ronchetti

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Marco Ronchetti is an author from Italy.

Publications

Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Domain independent semantic representation of multimedia presentations International Conference on Intelligent Networking and Collaborative Systems, INCoS 2009 English 2009 This paper describes a domain independent approach for semantically annotating and representing multimedia presentations. It uses a combination of techniques to automatically discover the content of the media and, though supervised or unsupervised methods, it can generate a RDF description out of it. The domain independence is achieved using Wikipedia as a source of knowledge instead of domain Ontologies. The described approach can be relevant for understanding multimedia content which can be used in Information Retrieval, categorization and summarization. 0 0
Extracting Semantics from Multimedia Content using Wikipedia English 2009 0 0
Using Wikipedia as a Reference for Extracting Semantic Information from a Text Semantic analysis
Clustering
Multi-words
Wikipedia
SEMAPRO English 2009 0 0
Using Wikipedia as a reference for extracting semantic information from a text Clustering
Multi-words
Semantic analysis
Wikipedia
3rd International Conference on Advances in Semantic Processing - SEMAPRO 2009 English 2009 In this paper we present an algorithm that, using Wikipedia as a reference, extracts semantic information from an arbitrary text. Our algorithm refines a procedure proposed by others, which mines all the text contained in the whole Wikipedia. Our refinement, based on a clustering approach, exploits the semantic information contained in certain types of Wikipedia hyperlinks, and also introduces an analysis based on multi-words. Our algorithm outperforms current methods in that the output contains many less false positives. We were also able to understand which (structural) part of the texts provides most of the semantic information extracted by the algorithm. 0 0
Discovering semantics in multimedia content using Wikipedia Content retrieval and filtering: Search over semi-structural Web sources
E-Learning
Multimedia
Wikipedia
Lecture Notes in Business Information Processing English 2008 Semantic-based information retrieval is an area of ongoing work. In this paper we present a solution for giving semantic support to multimedia content information retrieval in an e-Learning environment where very often a large number of multimedia objects and information sources are used in combination. Semantic support is given through intelligent use of Wikipedia in combination with statistical Information Extraction techniques. 0 0
Exploiting the Collective Intelligence Contained in Wikipedia to Automatically Describe the Content of a Document The Semantic Web: a view on data integration, reasoning, human factors, collective intelligence and technology adoption English 2008 The Wikipedia phenomenon very interesting from the point of view

of the collective, social effort to produce a large, strongly interlinked body of knowledge. It also offers, for the first time in history, a general source of information coded in electronic form and freely available to anyone. As such, it can be used as a reference for tools aiming at mining semantic meaning from generic documents. In this paper, we propose a clustering-based method that exploits some of the implicit knowledge built into Wikipedia to refine and

ameliorate existing approaches.
0 0
Intelligent mining and indexing of multi-language e-Learning material Content retrieval and filtering: Search over semi-structural Web sources
E-Learning
Multimedia
Wikipedia
Studies in Computational Intelligence English 2008 In this paper we describe a method to automatically discover important concepts and their relationships in e-Lecture material. The discovered knowledge is used to display semantic aware categorizations and query suggestions for facilitating navigation inside an unstructured multimedia repository of e-Lectures. We report about an implemented approach for dealing with learning materials referring to the same event in different languages. The information acquired from the speech is combined with the documents such as presentation slides, which are temporally synchronized with the video for creating new knowledge through a mapping with a taxonomy representation such as Wikipedia. 0 0