What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Machine learning
Ian H. Witten mostly deals with Artificial intelligence, Machine learning, Information retrieval, World Wide Web and Data mining.
The various areas that Ian H. Witten examines in his Artificial intelligence study include Pattern recognition and Natural language processing.
In the field of Machine learning, his study on Active learning and Decision tree learning overlaps with subjects such as Workbench and Generalization.
When carried out as part of a general Active learning research project, his work on Instance-based learning is frequently linked to work in Hyper-heuristic, therefore connecting diverse disciplines of study.
His World Wide Web study integrates concerns from other disciplines, such as Text mining, Ontology, Software and Semantics.
His studies deal with areas such as Graphical user interface, Set, Rule sets and Data science as well as Data mining.
His most cited work include:
- Data Mining: Practical Machine Learning Tools and Techniques (18817 citations)
- The WEKA data mining software: an update (15684 citations)
- Data mining: practical machine learning tools and techniques with Java implementations (4653 citations)
What are the main themes of his work throughout his whole career to date?
Ian H. Witten focuses on World Wide Web, Artificial intelligence, Information retrieval, Machine learning and Multimedia.
His World Wide Web study combines topics from a wide range of disciplines, such as User interface, Software and Interface.
His biological study spans a wide range of topics, including Pattern recognition, Data mining, Computer vision and Natural language processing.
His Information retrieval research is multidisciplinary, relying on both Document clustering and Index.
Machine learning is represented through his Instance-based learning, Decision tree and Active learning research.
His Data compression research is under the purview of Algorithm.
He most often published in these fields:
- World Wide Web (27.48%)
- Artificial intelligence (25.58%)
- Information retrieval (14.59%)
What were the highlights of his more recent work (between 2007-2019)?
- World Wide Web (27.48%)
- Artificial intelligence (25.58%)
- Information retrieval (14.59%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in World Wide Web, Artificial intelligence, Information retrieval, Software and Machine learning.
His World Wide Web study combines topics in areas such as User interface, Multimedia, Resource and Interface.
The study incorporates disciplines such as Key and Natural language processing in addition to Artificial intelligence.
His studies in Information retrieval integrate themes in fields like Hyperlink, Index and Document clustering.
In the subject of general Software, his work in Open source software and Software system is often linked to Workbench, thereby combining diverse domains of study.
His research investigates the link between Machine learning and topics such as Data mining that cross with problems in Field.
Between 2007 and 2019, his most popular works were:
- The WEKA data mining software: an update (15684 citations)
- Learning to link with wikipedia (1076 citations)
- An effective, low-cost measure of semantic relatedness obtained from Wikipedia links (636 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Programming language
Ian H. Witten mainly focuses on Artificial intelligence, Information retrieval, World Wide Web, Software and Semantic similarity.
Ian H. Witten interconnects IBM PC compatible, Machine learning, Key and Natural language processing in the investigation of issues within Artificial intelligence.
His Machine learning research includes elements of Algorithm and Data mining.
Ian H. Witten combines subjects such as Domain, Structure and Cluster analysis with his study of Information retrieval.
The concepts of his World Wide Web study are interwoven with issues in Ontology, User interface and Multimedia.
His research integrates issues of C4.5 algorithm, DSPACE and Stress testing in his study of Software.
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