Matches in ScholarlyData for { ?s ?p ?o. }
- item-4 hasContent paul-doran.
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- 501 creator bouke-huurnink.
- 501 creator edgar-meij.
- 501 creator laura-hollink.
- 501 creator maarten-de-rijke.
- 501 creator marc-bron.
- 501 type InProceedings.
- 501 label "Learning Semantic Query Suggestions".
- 501 sameAs 501.
- 501 abstract "An important application of semantic web technology is recognizing human-defined concepts in text. Query transformation is a strategy often used in search engines to derive queries that are able to return more useful search results than the original query and most popular search engines provide facilities that let users complete, specify, or reformulate their queries. We study the problem of semantic query suggestion, a special type of query transformation based on identifying semantic concepts contained in user queries. We use a feature-based approach in conjunction with supervised machine learning, augmenting term-based features with search history-based and concept-specific features. We apply our method to the task of linking queries from real-world query logs (the transaction logs of the Netherlands Institute for Sound and Vision) to the DBpedia knowledge base. We evaluate the utility of different machine learning algorithms, features, and feature types in identifying semantic concepts using a manually developed test bed and show significant improvements over an already high baseline. The resources developed for this paper, i.e., queries, human assessments, and extracted features, are available for download.".
- 501 hasAuthorList authorList.
- 501 hasTopic Semantic_Web.
- 501 isPartOf proceedings.
- 501 title "Learning Semantic Query Suggestions".
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- item-1 hasContent edgar-meij.
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- item-2 hasContent marc-bron.
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- item-5 hasContent maarten-de-rijke.
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- 524 creator anna-averbakh.
- 524 creator daniel-krause.
- 524 creator dimitrios-skoutas.
- 524 type InProceedings.
- 524 label "Exploiting User Feedback to Improve Semantic Web Service Discovery".
- 524 sameAs 524.
- 524 abstract "State-of-the-art discovery of Semantic Web services is based on hybrid algorithms that combine semantic and syntactic matchmaking. These approaches are purely based on similarity measures between parameters of a service request and available service descriptions, which, however, fail to completely capture the actual functionality of the service or the quality of the results returned by it. On the other hand, with the advent of Web 2.0, active user participation and collaboration has become an increasingly popular trend. Users often rate or group relevant items, thus providing valuable information that can be taken into account to further improve the accuracy of search results. In this paper, we tackle this issue, by proposing a method that combines multiple matching criteria with user feedback to further improve the results of the matchmaker. We extend a previously proposed dominance-based approach for service discovery, and describe how user feedback is incorporated in the matchmaking process. We evaluate the performance of our approach using a publicly available collection of OWL-S services.".
- 524 hasAuthorList authorList.
- 524 hasTopic Semantic_Web.
- 524 isPartOf proceedings.
- 524 title "Exploiting User Feedback to Improve Semantic Web Service Discovery".
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- item-1 hasContent anna-averbakh.
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- item-2 hasContent daniel-krause.
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- item-3 hasContent dimitrios-skoutas.
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- 105 creator jerome-david.
- 105 creator jerome-euzenat.
- 105 creator ondrej-svab-zamazal.
- 105 type InProceedings.
- 105 label "Ontology similarity in the alignment space".
- 105 sameAs 105.
- 105 abstract "Measuring similarity between ontologies can be very useful for different purposes, e.g., finding an ontology to replace another, or finding an ontology in which queries can be translated. Classical measures compute similarities or distances in an ontology space by directly comparing the content of ontologies. We introduce a new family of ontology measures computed in an alignment space: they evaluate the similarity between two ontologies with regard to the available alignments between them.We define two sets of such measures relying on the existence of a path between ontologies or on the ontology entities that are preserved by the alignments. The former accounts for known relations between ontologies, while the latter reflects the possibility to perform actions such as instance import or query translation. All these measures have been implemented in the OntoSim library, that has been used in experiments which showed that entity preserving measures are comparable to the best ontology space measures. Moreover, they showed a robust behaviour with respect to the alteration of the alignment space. ".
- 105 hasAuthorList authorList.
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- 105 keyword "semantic web".
- 105 title "Ontology similarity in the alignment space".
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- item-1 hasContent jerome-david.
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- item-3 hasContent ondrej-svab-zamazal.
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- 110 creator alasdair-j-g-gray.
- 110 creator jean-paul-calbimonte.
- 110 creator oscar-corcho.
- 110 type InProceedings.
- 110 label "Enabling Ontology-based Access to Streaming Data Sources".