TY - CONF AU - d'Aquin, Mathieu AU - Motta, Enrico A2 - T1 - Extracting relevant questions to an RDF dataset using formal concept analysis T2 - Proceedings of the sixth international conference on Knowledge capture PB - ACM C1 - New York, NY, USA PY - 2011/ CY - VL - IS - SP - 121 EP - 128 UR - http://doi.acm.org/10.1145/1999676.1999698 DO - 10.1145/1999676.1999698 KW - rdf KW - concept KW - formal KW - semantic KW - analysis KW - fca KW - ontology KW - web L1 - SN - 978-1-4503-0396-5 N1 - N1 - AB - With the rise of linked data, more and more semantically described information is being published online according to the principles and technologies of the Semantic Web (especially, RDF and SPARQL). The use of such standard technologies means that this data should be exploitable, integrable and reusable straight away. However, once a potentially interesting dataset has been discovered, significant efforts are currently required in order to understand its schema, its content, the way to query it and what it can answer. In this paper, we propose a method and a tool to automatically discover questions that can be answered by an RDF dataset. We use formal concept analysis to build a hierarchy of meaningful sets of entities from a dataset. These sets of entities represent answers, which common characteristics represent the clauses of the corresponding questions. This hierarchy can then be used as a querying interface, proposing questions of varying levels of granularity and specificity to the user. A major issue is however that thousands of questions can be included in this hierarchy. Based on an empirical analysis and using metrics inspired both from formal concept analysis and from ontology summarization, we devise an approach for identifying relevant questions to act as a starting point to the navigation in the question hierarchy. ER - TY - CONF AU - Angeletou, Sofia AU - Sabou, Marta AU - Motta, Enrico A2 - T1 - Semantically enriching folksonomies with FLOR T2 - Proceedings of the CISWeb Workshop, located at the 5th European Semantic Web Conference ESWC 2008 PB - C1 - PY - 2008/ CY - VL - IS - SP - EP - UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.2569 DO - KW - ol_web2.0 KW - ontology_learning KW - semantic_enrichment L1 - SN - N1 - Scientific Commons: Semantically enriching folksonomies with FLOR (2008), 2008 [Sofia Angeletou, Marta Sabou, Enrico Motta] N1 - AB - Abstract. While the increasing popularity of folksonomies has lead to a vast quantity of tagged data, resource retrieval in folksonomies is limited by being agnostic to the meaning (i.e., semantics) of tags. Our goal is to automatically enrich folksonomy tags (and implicitly the related resources) with formal semantics by associating them to relevant concepts defined in online ontologies. We introduce FLOR, a method that performs automatic folksonomy enrichment by combining knowledge from WordNet and online available ontologies. Experimentally testing FLOR, we found that it correctly enriched 72 % of 250 Flickr photos. 1 ER - TY - CONF AU - Angeletou, Sofia AU - Sabou, Marta AU - Motta, Enrico A2 - T1 - Semantically enriching folksonomies with FLOR T2 - In Proc of the 5th ESWC. workshop: Collective Intelligence & the Semantic Web PB - C1 - PY - 2008/ CY - VL - IS - SP - EP - UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.2569 DO - KW - tagging KW - taggingsurvey KW - ontologies KW - semantic KW - folksonomy L1 - SN - N1 - Semantically enriching folksonomies with FLOR N1 - AB - Abstract. While the increasing popularity of folksonomies has lead to a vast quantity of tagged data, resource retrieval in folksonomies is limited by being agnostic to the meaning (i.e., semantics) of tags. Our goal is to automatically enrich folksonomy tags (and implicitly the related resources) with formal semantics by associating them to relevant concepts defined in online ontologies. We introduce FLOR, a method that performs automatic folksonomy enrichment by combining knowledge from WordNet and online available ontologies. Experimentally testing FLOR, we found that it correctly enriched 72 % of 250 Flickr photos. 1 ER - TY - CONF AU - Specia, Lucia AU - Motta, Enrico A2 - T1 - Integrating Folksonomies with the Semantic Web T2 - PB - Springer Berlin / Heidelberg C1 - PY - 2007/ CY - VL - 4519/2007 IS - SP - 624 EP - 639 UR - DO - KW - ol_web2.0 KW - methods_concepts KW - toread_dbe KW - toread KW - emergentsemantics_evidence L1 - SN - N1 - N1 - AB - While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of groups of concepts and partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the del.icio.us and Flickr tag sets show that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies and meaningful relationships among subsets of these tags can be identified. ER - TY - GEN AU - Specia, Lucia AU - Motta, Enrico A2 - T1 - Integrating Folksonomies with the Semantic Web JO - PB - Springer Berlin / Heidelberg C1 - PY - 2007/ VL - 4519/2007 IS - SP - 624 EP - 639 UR - DO - KW - ol_web2.0 KW - toread L1 - N1 - N1 - AB - While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of groups of concepts and partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the del.icio.us and Flickr tag sets show that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies and meaningful relationships among subsets of these tags can be identified. ER - TY - CONF AU - Specia, Lucia AU - Motta, Enrico A2 - Franconi, Enrico A2 - Kifer, Michael A2 - May, Wolfgang T1 - Integrating Folksonomies with the Semantic Web T2 - Proceedings of the European Semantic Web Conference (ESWC2007) PB - Springer-Verlag C1 - Berlin Heidelberg, Germany PY - 2007/07 CY - VL - 4519 IS - SP - 624 EP - 639 UR - http://www.eswc2007.org/pdf/eswc07-specia.pdf DO - KW - 2007 KW - semantic KW - folksonomy KW - eswc KW - web L1 - SN - N1 - N1 - AB - While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the Del.icio.us and Flickr tag sets showed that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies, and meaningful relationships among subsets of these tags can be identified. ER - TY - CONF AU - Lei, Yuangui AU - Sabou, Marta AU - Lopez, Vanessa AU - Zhu, Jianhan AU - Uren, Victoria AU - Motta, Enrico A2 - T1 - An Infrastructure for Acquiring High Quality Semantic Metadata. T2 - ESWC PB - C1 - PY - 2006/ CY - VL - IS - SP - 230 EP - 244 UR - DO - KW - european KW - proceedings KW - 2006 KW - semantic KW - conference KW - learning KW - eswc KW - ontology KW - web L1 - SN - N1 - DBLP Record 'conf/esws/LeiSLZUM06' N1 - AB - ER - TY - CONF AU - Lopez, Vanessa AU - Motta, Enrico AU - Uren, Victoria A2 - T1 - PowerAqua: Fishing the Semantic Web. T2 - ESWC PB - C1 - PY - 2006/ CY - VL - IS - SP - 393 EP - 410 UR - DO - KW - searching KW - european KW - proceedings KW - 2006 KW - semantic KW - conference KW - querying KW - eswc KW - and KW - web L1 - SN - N1 - DBLP Record 'conf/esws/LopezMU06' N1 - AB - ER -