His scientific interests lie mostly in Information retrieval, Probabilistic logic, Ranking, Artificial intelligence and Search engine indexing. His study on Information retrieval is mostly dedicated to connecting different topics, such as XML retrieval. His Divergence-from-randomness model study in the realm of Probabilistic logic interacts with subjects such as String metric.
The study incorporates disciplines such as XML, Data mining and Pattern recognition in addition to Ranking. His Artificial intelligence research includes themes of Machine learning and Natural language processing. The various areas that Norbert Fuhr examines in his Search engine indexing study include Rule-based system and Relevance feedback.
Norbert Fuhr focuses on Information retrieval, Probabilistic logic, World Wide Web, Relevance and XML. His research on Information retrieval often connects related topics like XML retrieval. His Probabilistic logic research incorporates elements of Datalog and Data mining.
His World Wide Web research is multidisciplinary, relying on both User interface and Multimedia. His Relevance research is multidisciplinary, incorporating perspectives in Document retrieval and Vector space model. His studies deal with areas such as Test and Relevance feedback as well as XML.
Norbert Fuhr mainly focuses on Information retrieval, Reproducibility, Artificial intelligence, Natural language processing and Data science. He is interested in Ranking, which is a field of Information retrieval. Norbert Fuhr works mostly in the field of Reproducibility, limiting it down to topics relating to Data mining and, in certain cases, Face and Field, as a part of the same area of interest.
His research integrates issues of Machine learning and Markov model in his study of Artificial intelligence. His research investigates the connection between Natural language processing and topics such as Recommender system that intersect with problems in Predictive modelling. The study incorporates disciplines such as Test and Context in addition to Data science.
The scientist’s investigation covers issues in Reproducibility, Information retrieval, Information system, Data science and Recommender system. He has researched Information retrieval in several fields, including Session, Information needs and Result set. Norbert Fuhr undertakes interdisciplinary study in the fields of Data science and e-Science through his research.
His Recommender system research includes elements of Predictive modelling and Performance prediction. His work carried out in the field of Predictive modelling brings together such families of science as Artificial intelligence and Natural language processing. Markov chain connects with themes related to Data mining in his study.
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.
A probabilistic relational algebra for the integration of information retrieval and database systems
Norbert Fuhr;Thomas Rölleke.
ACM Transactions on Information Systems (1997)
Probabilistic models in information retrieval
The Computer Journal (1992)
XIRQL: a query language for information retrieval in XML documents
Norbert Fuhr;Kai Großjohann.
international acm sigir conference on research and development in information retrieval (2001)
A probabilistic learning approach for document indexing
Norbert Fuhr;Chris Buckley.
international acm sigir conference on research and development in information retrieval (1991)
Evaluation of digital libraries
Norbert Fuhr;Giannis Tsakonas;Trond Aalberg;Maristella Agosti.
International Journal on Digital Libraries (2007)
Models for retrieval with probabilistic indexing
Information Processing and Management (1989)
Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002
James Allan;Jay Aslam;Nicholas Belkin;Chris Buckley.
international acm sigir conference on research and development in information retrieval (2003)
A decision-theoretic approach to database selection in networked IR
ACM Transactions on Information Systems (1999)
Probabilistic Datalog—a logic for powerful retrieval methods
international acm sigir conference on research and development in information retrieval (1995)
Advances in XML Information Retrieval and Evaluation
Norbert Fuhr;Mounia Lalmas;Saadia Malik;Gabriella Kazai.
Profile was last updated on December 6th, 2021.
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