What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- The Internet
Andreas Rauber focuses on Self-organizing map, Artificial intelligence, Multimedia, Structure and Artificial neural network.
The concepts of his Self-organizing map study are interwoven with issues in Visualization, Data mining and Human–computer interaction.
The Data mining study combines topics in areas such as Representation, Set and Data set.
His Artificial intelligence research includes themes of Machine learning, Task, Pattern recognition and Natural language processing.
His research investigates the connection between Multimedia and topics such as Convolutional neural network that intersect with problems in Deep learning.
His Information retrieval research focuses on Music information retrieval and how it relates to Musical composition and Popular music.
His most cited work include:
- The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data (392 citations)
- Content-based organization and visualization of music archives (275 citations)
- The growing hierarchical self-organizing map (220 citations)
What are the main themes of his work throughout his whole career to date?
Andreas Rauber mainly focuses on Information retrieval, World Wide Web, Artificial intelligence, Digital preservation and Data mining.
His Information retrieval research incorporates themes from Music information retrieval and Cluster analysis.
His World Wide Web study incorporates themes from Multimedia and Interface.
Andreas Rauber has included themes like Machine learning, Pattern recognition and Natural language processing in his Artificial intelligence study.
The study incorporates disciplines such as Set and Data set in addition to Data mining.
His work on Self-organizing map as part of general Artificial neural network study is frequently linked to Structure, bridging the gap between disciplines.
He most often published in these fields:
- Information retrieval (22.44%)
- World Wide Web (18.56%)
- Artificial intelligence (17.17%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (17.17%)
- Information retrieval (22.44%)
- Data science (8.86%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Information retrieval, Data science, World Wide Web and Data mining.
His study in Artificial intelligence focuses on Artificial neural network in particular.
Andreas Rauber interconnects Recall, Graph and Information system in the investigation of issues within Information retrieval.
Andreas Rauber focuses mostly in the field of Data science, narrowing it down to matters related to Context and, in some cases, Workflow.
Andreas Rauber does research in World Wide Web, focusing on Digital preservation specifically.
His Data mining research integrates issues from Data citation and Data set.
Between 2014 and 2021, his most popular works were:
- Achieving human and machine accessibility of cited data in scholarly publications (75 citations)
- LifeCLEF 2015: Multimedia Life Species Identification Challenges (48 citations)
- Reproducibility of Data-Oriented Experiments in e-Science (Dagstuhl Seminar 16041) (35 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- The Internet
His primary areas of study are Information retrieval, Artificial intelligence, Convolutional neural network, Reproducibility and Identification.
His Information retrieval study which covers Domain that intersects with Speech recognition and Support vector machine.
His study connects Natural language processing and Artificial intelligence.
His research in Convolutional neural network intersects with topics in Multimedia and Task.
His Multimedia research is multidisciplinary, incorporating perspectives in Visual music, Pop music automation and Music information retrieval.
Andreas Rauber usually deals with Artificial neural network and limits it to topics linked to Layer and Metadata.
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