Francesco Ronzano

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Francesco Ronzano 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
Editing knowledge resources: The wiki way Collaborative editing web applications
Knowledge resources
Web and social knowledge management
Wiki paradigm
International Conference on Information and Knowledge Management, Proceedings English 2011 The creation, customization, and maintenance of knowledge resources are essential for fostering the full deployment of Language Technologies. The definition and refinement of knowledge resources are time- and resource-consuming activities. In this paper we explore how the Wiki paradigm for online collaborative content editing can be exploited to gather massive social contributions from common Web users in editing knowledge resources. We discuss the Wikyoto Knowledge Editor, also called Wikyoto. Wikyoto is a collaborative Web environment that enables users with no knowledge engineering background to edit the multilingual network of knowledge resources exploited by KYOTO, a cross-lingual text mining system developed in the context of the KYOTO European Project. 0 0
Editing knowledge resources: the wiki way Collaborative editing web applications
Knowledge resources
Web and social knowledge management
Wiki paradigm
CIKM English 2011 0 0
Extracting events from Wikipedia as RDF triples linked to widespread semantic web datasets Knowledge Extraction
Knowledge representation
Natural Language Processing
Semantic web
Semantics
Lecture Notes in Computer Science English 2011 Many attempts have been made to extract structured data from Web resources, exposing them as RDF triples and interlinking them with other RDF datasets: in this way it is possible to create clouds of highly integrated Semantic Web data collections. In this paper we describe an approach to enhance the extraction of semantic contents from unstructured textual documents, in particular considering Wikipedia articles and focusing on event mining. Starting from the deep parsing of a set of English Wikipedia articles, we produce a semantic annotation compliant with the Knowledge Annotation Format (KAF). We extract events from the KAF semantic annotation and then we structure each event as a set of RDF triples linked to both DBpedia and WordNet. We point out examples of automatically mined events, providing some general evaluation of how our approach may discover new events and link them to existing contents. 0 0
Extracting events from wikipedia as RDF triples linked to widespread semantic web datasets Knowledge Extraction
Knowledge representation
Natural Language Processing
Semantic web
Semantics
OCSC English 2011 0 0
Semantify del.icio.us: Automatically turn your tags into senses CEUR Workshop Proceedings English 2008 At present tagging is experimenting a great diffusion as the most adopted way to collaboratively classify resources over the Web. In this paper, after a detailed analysis of the attempts made to improve the organization and structure of tagging systems as well as the usefulness of this kind of social data, we propose and evaluate the Tag Disambiguation Algorithm, mining del.icio.us data. It allows to easily semantify the tags of the users of a tagging service: it automatically finds out for each tag the related concept of Wikipedia in order to describe Web resources through senses. On the basis of a set of evaluation tests, we analyze all the advantages of our sense-based way of tagging, proposing new methods to keep the set of users tags more consistent or to classify the tagged resources on the basis of Wikipedia categories, YAGO classes or Wordnet synsets. We discuss also how our semanitified social tagging data are strongly linked to DBPedia and the datasets of the Linked Data community. 0 0
Tagpedia: A semantic reference to describe and search for Web resources Data mining
Semantics
Social
Web
Wikipedia
CEUR Workshop Proceedings English 2008 Nowadays the Web represents a growing collection of an enormous amount of contents where the need for better ways to find and organize the available data is becoming a fundamental issue, in order to deal with information overload. Keyword based Web searches are actually the preferred mean to seek for contents related to a specific topic. Search engines and collaborative tagging systems make possible the search for information thanks to the association of descriptive keywords to Web resources. All of them show problems of inconsistency and consequent reduction of recall and precision of searches, due to polysemy, synonymy and in general all the different lexical forms that can be used to refer to a particular meaning. A possible way to face or at least reduce these problems is represented by the introduction of semantics to characterize the contents of Web resources: each resource is described by one or more concepts instead of simple and often ambiguous keywords. To support these task the availability of a global semantic resource of reference is fundamental. On the basis of our past experience with the semantic tagging of Web resources and the SemKey Project, we are developing Tagpedia, a general-domain "encyclopedia" of tags, semantically structured for generating semantic descriptions of contents over the Web, created by mining Wikipedia. In this paper, starting from an analysis of the weak points of non-semantic keyword based Web searches, we introduce our idea of semantic characterization of Web resources describing the structure and organization of Tagpedia. We introduce our first realization of Tagpedia, suggesting all the possible improvements that can be carried out in order to exploit its full potential. 0 0