Matches in ScholarlyData for { ?s ?p ?o. }
- 17 keyword "web science".
- 17 title "Towards Trust in Web Content Using Semantic Web Technologies".
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- item-1 hasContent qi-gao.
- 19 creator mathew-joseph.
- 19 type InProceedings.
- 19 label "A Contextualized Knowledge Framework for SemanticWeb".
- 19 sameAs 19.
- 19 abstract "This thesis focuses on developing an efficient framework for contextualized knowledge representation on Semantic Web. We bring about the drawbacks of existing context formalisms which hinders an efficient implementation and propose a formalism for contexts that enables for the development of framework with desired properties. Some of the future milestones to be achieved for this thesis work are (i) develop a proof theory for the logical framework based on Description Logics (DL) (ii) developing reasoning algorithms (iii) verify and compare the performance of these algorithms to existing distributed reasoning formalisms and (iv) system implementation".
- 19 hasAuthorList authorList.
- 19 isPartOf proceedings.
- 19 keyword "contexts".
- 19 keyword "contextualized knowledge representation".
- 19 keyword "ontology".
- 19 keyword "reasoning".
- 19 keyword "semantic web".
- 19 title "A Contextualized Knowledge Framework for SemanticWeb".
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- item-1 type ListItem.
- item-1 hasContent mathew-joseph.
- 22 creator georgeta-bordea.
- 22 type InProceedings.
- 22 label "Concept Extraction Applied to the Task of Expert Finding".
- 22 sameAs 22.
- 22 abstract "The Semantic Web uses formal ontologies as a key instrument that adds structure to the underlying data, but building domain specific ontologies is still a difficult, time consuming and error-prone process because most information is currently available as free-text or semi-structured text. Therefore the development of fast and cheap solutions for ontology learning from text is a key factor for the success and large scale adoption of the Semantic Web. Ontology development is primarily concerned with the definition of concepts and relations between them, so one of the fundamental research problems related to ontology learning is the reliable extraction of concepts from text. To investigate this research problem we will focus on the expert finding application, i.e. the reliable extraction of expertise topics from relevant text that can be assigned to individuals in an organization.".
- 22 hasAuthorList authorList.
- 22 isPartOf proceedings.
- 22 keyword "concept extraction".
- 22 keyword "expertise mining".
- 22 keyword "expertise topics".
- 22 keyword "information extraction".
- 22 keyword "text mining".
- 22 title "Concept Extraction Applied to the Task of Expert Finding".
- authorList type List.
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- item-1 type ListItem.
- item-1 hasContent georgeta-bordea.
- 23 creator claudia-wagner.
- 23 type InProceedings.
- 23 label "Exploring the Wisdom of the Tweets: Knowledge Acquisition from Social Awareness Streams".
- 23 sameAs 23.
- 23 abstract "Although one might argue that little wisdom can be conveyed in messages of 140 characters or less, this PhD research sets out to explore if and what kind of knowledge can be acquired from different aggregations of social awareness streams. The expected contribution of this research is a network-theoretic model for defining, comparing and analyzing different kinds of social awareness streams and an experimental prototype to extract semantic models from them.".
- 23 hasAuthorList authorList.
- 23 isPartOf proceedings.
- 23 keyword "Knowledge Acquisition".
- 23 keyword "Microblogs".
- 23 keyword "Semantic Analysis".
- 23 keyword "Social Web".
- 23 title "Exploring the Wisdom of the Tweets: Knowledge Acquisition from Social Awareness Streams".
- authorList type List.
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- item-1 type ListItem.
- item-1 hasContent claudia-wagner.
- 25 creator jacopo-urbani.
- 25 type InProceedings.
- 25 label "Scalable reasoning in the Semantic Web".
- 25 sameAs 25.
- 25 abstract "The current state of the art regarding scalable reasoning consists of programs that run on a single machine. When the amount of data is too large, or the logic is too complex, the computational resources of a single machine are not enough. We propose a distributed approach that overcomes these limitations and we sketch a research methodology. A distributed approach is challenging because of the skew in data distribution and the difficulty in partitioning Semantic Web data. We present initial results which are promising and suggest that the approach may be successful.".
- 25 hasAuthorList authorList.
- 25 isPartOf proceedings.
- 25 keyword "MapReduce".
- 25 keyword "distributed".
- 25 keyword "reasoning".
- 25 keyword "rule based".
- 25 keyword "scalable".
- 25 title "Scalable reasoning in the Semantic Web".
- authorList type List.
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- item-1 hasContent jacopo-urbani.
- 30 creator sebastian-hellmann.
- 30 type InProceedings.
- 30 label "The Semantic Gap of Formalized Meaning".
- 30 sameAs 30.
- 30 abstract "Recent work in Ontology Learning and Textmining mainly focused on engineering methods to solve practical problem. In this thesis, we investigate methods that can substantially improve a wide range of existing approaches by minimizing the underlying problem: The Semantic Gap between formalized meaning and human cognition. We deploy OWL as a Meaning Representation Language and create a unified model, which combines existing NLP methods with Linguistic knowledge and aggregates disambiguated background knowledge from the Web of Data. The presented methodology allows to study and evaluate the capabilities of such aggregated knowledge to improve the efficiency of methods in Ontology Learning.".
- 30 hasAuthorList authorList.
- 30 isPartOf proceedings.
- 30 keyword "DBpedia".
- 30 keyword "Machine Learning".
- 30 keyword "NLP".
- 30 keyword "OWL".
- 30 keyword "Ontology Learning".
- 30 title "The Semantic Gap of Formalized Meaning".
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