Aldo Gangemi

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Aldo Gangemi is an author.


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
Aemoo: Exploring knowledge on the Web Proceedings of the 3rd Annual ACM Web Science Conference, WebSci 2013 English 2013 Aemoo is a Semantic Web application supporting knowledge exploration on the Web. Through a keyword-based search interface, users can gather an effective summary of the knowledge about an entity, according to Wikipedia, Twitter, and Google News. Summaries are designed by applying lenses based on a set of empirically discovered knowledge patterns. Copyright 2013 ACM. 0 0
Tìpalo: A tool for automatic typing of DBpedia entities Lecture Notes in Computer Science English 2013 In this paper we demonstrate the potentiality of Tìpalo, a tool for automatically typing DBpedia entities. Tìpalo identifies the most appropriate types for an entity in DBpedia by interpreting its definition extracted from its corresponding Wikipedia abstract. Tìpalo relies on FRED, a tool for ontology learning from natural language text, and on a set of graph-pattern-based heuristics which work on the output returned by FRED in order to select the most appropriate types for a DBpedia entity. The tool returns a RDF graph composed of rdf:type, rdfs:subClassOf, owl:sameAs, and owl:equivalentTo statements providing typing information about the entity. Additionally the types are aligned to two lists of top-level concepts, i.e., Wordnet supersenses and a subset of DOLCE Ultra Lite classes. Tìpalo is available as a Web-based tool and exposes its API as HTTP REST services. 0 0
Automatic typing of DBpedia entities Lecture Notes in Computer Science English 2012 We present Tìpalo, an algorithm and tool for automatically typing DBpedia entities. Tìpalo identifies the most appropriate types for an entity by interpreting its natural language definition, which is extracted from its corresponding Wikipedia page abstract. Types are identified by means of a set of heuristics based on graph patterns, disambiguated to WordNet, and aligned to two top-level ontologies: WordNet supersenses and a subset of DOLCE+DnS Ultra Lite classes. The algorithm has been tuned against a golden standard that has been built online by a group of selected users, and further evaluated in a user study. 0 0
Type inference through the analysis of wikipedia links CEUR Workshop Proceedings English 2012 DBpedia contains millions of untyped entities, either if we consider the native DBpedia ontology, or Yago plus Word- Net. Is it possible to automatically classify those entities? Based on previous work on wikilink invariances, we wondered if wikilinks convey a knowledge rich enough for their classification. In this paper we give three contributions. Concerning the DBpedia link structure, we describe some measurements and notice both problems (e.g. the bias that could be induced by the incomplete ontological coverage of the DBpedia ontology), and potentials existing in current type coverage. Concerning classification, we present two techniques that exploit wikilinks, one based on induction from machine learning techniques, and the other on abducfition. Finally, we discuss the limited results of classification, which confrmed our fears expressed in the description of general figures from the measurement. We also suggest some new possible directions to entity classification that could be taken. 0 0
Encyclopedic knowledge patterns from wikipedia links ISWC English 2011 0 0
Acquiring thesauri from wikis by exploiting domain models and lexical substitution ESWC English 2010 0 0