BibSonomy publications for /author/ZaihrayeuSun Feb 12 00:00:00 CET 2012LDHconf/ijcai/2011ldl8-13Sense Induction in Folksnonomies.2011dblp Fri Nov 25 00:00:00 CET 2011Encyclopedia of Database Systemsreference/db/20091613-1619Lightweight Ontologies.2009dblp Sun Nov 20 00:00:00 CET 2011I-SEMANTICSconf/i-semantics/2011179-182ACM International Conference Proceeding SeriesAdopting semantic annotation systems for corporate portal management: a Telefonica case study.2011dblp Mon Nov 07 00:00:00 CET 2011NLP4DL/AT4DLconf/ircdl/2009nlp114-134Lecture Notes in Computer ScienceSemantic Disambiguation in Folksonomy: A Case Study.66992009dblp Wed Aug 03 10:31:15 CEST 2011Proc. of the 6th European Semantic Web Conf. (ESWC2009)429--444Concept search2009imported Fri Jul 29 13:36:54 CEST 2011Proceedings of ESWC 2011June2476-480LNCSSemantic Annotation of Images on Flickr66442011annotation flickr folksonomy images semanticweb In this paper we introduce an application that allows its users to have an explicit control on the meaning of tags they use when uploading photos on Flickr. In fact, this application provides to the users an improved interface with which they can add concepts to photos instead of simple free-text tags. They can thus directly provide semantic tags for their photos that can then be used to improve services such as search.Mon Jul 04 00:00:00 CEST 2011CIAconf/cia/200218-35Lecture Notes in Computer ScienceMaking Peer Databases Interact - A Vision for an Architecture Supporting Data Coordination.24462002dblp Tue May 10 10:49:57 CEST 2011Workshop on Discovering Meaning On the Go in Large Heterogeneous Data 2011Sense Induction in Folksonomies2011algorithm disambiguation evauation induction semantic semanticweb sense wordnet Folksonomies, often known as tagging systems, such as the ones used on the popular Delicious or flickr websites, use a very simple knowledge organisation system. Users are thus quick to adopt this system and create extensive knowledge annotations on the Web. However, because of the simplicity of the folksonomy model, the semantics of the tags used is not explicit and can only be inferred from the context of use of the tags. This is a barrier for the automatic use of such knowledge organisation systems by computers and new techniques have to be developed to extract the semantic of the tags used. In this paper we discuss an algorithm to detect new senses of terms in a folksonomy; we also propose a formal evaluation methodology that will enable to compare results between different approaches in the field. This work has been partially supported by INSEMTIVES project (FP7-231181, see http://www.insemtives.eu).Thu Apr 14 07:06:28 CEST 2011 DIT-07-071 Lightweight Ontologies Technical Report 2007imported Thu Apr 14 07:06:28 CEST 2011 DIT-07-029 From Web Directories to Ontologies: Natural Language Processing Challenges Technical Report 2007imported Wed Apr 06 16:01:21 CEST 2011Proceedings of ESWC 2011June2476-480LNCSSemantic Annotation of Images on Flickr66442011demo flickr folksonomy insemtives In this paper we introduce an application that allows its users to have an explicit control on the meaning of tags they use when uploading photos on Flickr. In fact, this application provides to the users an improved interface with which they can add concepts to photos instead of simple free-text tags. They can thus directly provide semantic tags for their photos that can then be used to improve services such as search.Wed Apr 06 15:47:15 CEST 2011Lecture Notes on Computer Science), Hot Topic sublineSemantic Disambiguation in Folksonomy: a Case Study66992011digitallibrary disambiguation folksonomy preprocessing semantic semanticweb tagging Social annotation systems such as del.icio.us, Flickr and others have gained tremendous popularity among Web 2.0 users. One of the factors of success was the simplicity of the underlying model, which consists of a resource (e.g., a web page), a tag (e.g., a text string), and a user who annotates the resource with the tag. However, due to the syntactic nature of the underlying model, these systems have been criticised for not being able to take into account the explicit semantics implicitly encoded by the users in each tag. In this article we: a) provide a formalisation of an annotation model in which tags are based on concepts instead of being free text strings; b) describe how an existing annotation system can be converted to the proposed model; c) report on the results of such a conversion on the example of a del.icio.us dataset; and d) show how the quality of search can be improved by the semantic in the converted dataset. Fri Nov 26 09:32:26 CET 2010DIT-07-029From Web Directories to Ontologies: Natural Language Processing ChallengesTechnical Report2007imported Fri Nov 26 09:32:26 CET 2010DIT-07-071Lightweight OntologiesTechnical Report2007imported Fri May 29 11:44:15 CEST 20096th Annual European Semantic Web Conference (ESWC2009)June429-444Concept Search2009Query Search_Engine Semantic_Continuum Semantic_Inverted_Index Semantic_Search Semantic_Web Visualization In this paper we present a novel approach, called Concept Search, which extends syntactic search, i.e., search based on the computation of string similarity between words, with semantic search, i.e., search based on the computation of semantic relations among concepts. The key idea of Concept Search is to operate on complex concepts and to maximally exploit the semantic information available, reducing to syntactic search only when necessary, i.e., when no semantic information is available. The experimental results show that Concept Search performs at least as well as syntactic search, improving the quality of results as a function of the amount of available semantics.Sat May 23 00:00:00 CEST 2009ESWCconf/esws/2009429-444Lecture Notes in Computer ScienceConcept Search.55542009dblp Mon Mar 16 13:27:57 CET 2009Proceedings of the Workshop on Semantic Search (SemSearch 2008) at the 5th European Semantic Web Conference (ESWC 2008) , June 2, 2008, Tenerife, SpainCEUR Workshop ProceedingsConcept Search: Semantics Enabled Syntactic Search3342008search semsearch syntactic_search workshop Sun Mar 01 17:41:13 CET 2009Journal on Data Semantics VIII57--81Encoding Classifications into Lightweight Ontologies2007diplomarbeit onotologies Classifications have been used for centuries with the goal of cataloguing and searching large sets of objects. In the early days it was mainly books; lately it has also become Web pages, pictures and any kind of digital resources. Classificationsdescribe their contents using natural language labels, an approach which has proved very effective in manual classification.However natural language labels show their limitations when one tries to automate the process, as they make it very hard toreason about classifications and their contents. In this paper we introduce the novel notion of Formal Classification, as a graph structure where labels are written in a propositional concept language. Formal Classifications turn out to besome form of lightweight ontologies. This, in turn, allows us to reason about them, to associate to each node a normal formformula which univocally describes its contents, and to reduce document classification and query answering to reasoning aboutsubsumption.Fri Feb 13 13:22:04 CET 2009The Semantic Web623--636From Web Directories to Ontologies: Natural Language Processing Challenges2008aswc07, iswc07 Hierarchical classifications are used pervasively by humans as a means to organize their data and knowledge about the world. One of their main advantages is that natural language labels, used to describe their contents, are easily understood by human users. However, at the same time, this is also one of their main disadvantages as these same labels are ambiguous and very hard to be reasoned about by software agents. This fact creates an insuperable hindrance for classifications to being embedded in the Semantic Web infrastructure. This paper presents an approach to converting classifications into lightweight ontologies, and it makes the following contributions: (i) it identifies the main NLP problems related to the conversion process and shows how they are different from the classical problems of NLP; (ii) it proposes heuristic solutions to these problems, which are especially effective in this domain; and (iii) it evaluates the proposed solutions by testing them on DMoz data.Fri Jun 06 00:00:00 CEST 2008SemSearchconf/esws/2008semsearch109-123CEUR Workshop ProceedingsConcept Search: Semantics Enabled Syntactic Search.3342008dblp