2023 - Research.com Computer Science in Germany Leader Award
His primary areas of investigation include Information retrieval, Ontology, Artificial intelligence, Natural language processing and Process ontology. His Information retrieval research incorporates themes from Concept search and Information needs. His Ontology research incorporates elements of Ontology, World Wide Web and Information integration.
His work in Artificial intelligence addresses issues such as Formal concept analysis, which are connected to fields such as Data analysis and Parsing. His Natural language processing research includes themes of Interface description language, Context, Cluster analysis and Taxonomy. His biological study spans a wide range of topics, including Ontology-based data integration and Upper ontology.
Philipp Cimiano mainly investigates Artificial intelligence, Natural language processing, Information retrieval, Ontology and World Wide Web. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Context, Machine learning and Task. His research on Information retrieval often connects related areas such as Annotation.
His Ontology research extends to the thematically linked field of Ontology. His studies deal with areas such as RDF and Data science as well as Linked data. His Social Semantic Web study integrates concerns from other disciplines, such as Semantic Web Stack and Semantic search.
His primary areas of study are Artificial intelligence, Natural language processing, Linked data, Ontology and Information retrieval. His research in Artificial intelligence intersects with topics in Machine learning and Task. His Natural language processing research integrates issues from Knowledge base and Semantic Web.
His research integrates issues of Metadata and Data science in his study of Linked data. His study in the field of Ontology alignment, Suggested Upper Merged Ontology and Ontology-based data integration is also linked to topics like Spinal cord injury. His study on Information retrieval is mostly dedicated to connecting different topics, such as Ontology.
Philipp Cimiano mostly deals with Artificial intelligence, Natural language processing, Question answering, Linked data and Word. Philipp Cimiano interconnects Context, Machine learning and Use case in the investigation of issues within Artificial intelligence. The various areas that he examines in his Natural language processing study include Ontology and Commonsense knowledge, Knowledge base.
In the field of Ontology, his study on Suggested Upper Merged Ontology overlaps with subjects such as Spinal cord injury. His Question answering study deals with the bigger picture of Information retrieval. His work carried out in the field of Linked data brings together such families of science as Representation and Metadata.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Ontology Learning and Population from Text: Algorithms, Evaluation and Applications
Learning concept hierarchies from text corpora using formal concept analysis
Philipp Cimiano;Andreas Hotho;Steffen Staab.
Journal of Artificial Intelligence Research (2005)
Semantic annotation for knowledge management: Requirements and a survey of the state of the art
Victoria Uren;Philipp Cimiano;José Iria;Siegfried Handschuh.
Journal of Web Semantics (2006)
Text2Onto: a framework for ontology learning and data-driven change discovery
Philipp Cimiano;Johanna Völker.
international conference natural language processing (2005)
Template-based question answering over RDF data
Christina Unger;Lorenz Bühmann;Jens Lehmann;Axel-Cyrille Ngonga Ngomo.
the web conference (2012)
Ontology Learning from Text: Methods, Evaluation and Applications
B. Magnini;P. Buitelaar;P. Cimiano.
Towards the self-annotating web
Philipp Cimiano;Siegfried Handschuh;Steffen Staab.
the web conference (2004)
Ontology Learning from Text: An Overview
Paul Buitelaar;Philipp Cimiano;Bernardo Magnini.
Ontology Learning from Text: Methods, Evaluation and Applications (2005)
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data
Thanh Tran;Haofen Wang;Sebastian Rudolph;Philipp Cimiano.
international conference on data engineering (2009)
Natural language interfaces : what's the problem? -a data-driven quantitative analysis
Philipp Cimiano;Michael Minock.
Lecture Notes in Computer Science (2010)
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