What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Machine learning
His scientific interests lie mostly in Artificial intelligence, Natural language processing, Information retrieval, Affect and World Wide Web.
His study in Artificial intelligence focuses on Verb in particular.
His biological study deals with issues like Principle of compositionality, which deal with fields such as Writing style and State.
His research investigates the connection with Information retrieval and areas like Web mining which intersect with concerns in Information extraction and Relation.
His studies in Affect integrate themes in fields like Human–computer interaction, Avatar, User interface and Expression.
His World Wide Web study combines topics from a wide range of disciplines, such as Human–computer information retrieval and Relevance.
His most cited work include:
- KEYWORD EXTRACTION FROM A SINGLE DOCUMENT USING WORD CO-OCCURRENCE STATISTICAL INFORMATION (650 citations)
- Measuring Semantic Similarity between Words Using Web Search Engines (527 citations)
- THE EMPATHIC COMPANION: A CHARACTER-BASED INTERFACE THAT ADDRESSES USERS' AFFECTIVE STATES (202 citations)
What are the main themes of his work throughout his whole career to date?
Mitsuru Ishizuka mostly deals with Artificial intelligence, Natural language processing, Information retrieval, World Wide Web and Multimedia.
His Artificial intelligence research integrates issues from Machine learning, Computer vision and Pattern recognition.
The various areas that Mitsuru Ishizuka examines in his Natural language processing study include Rhetorical Structure Theory and Rhetorical question.
All of his Information retrieval and Social Semantic Web, Semantic computing, Semantic search, Search engine and Relationship extraction investigations are sub-components of the entire Information retrieval study.
His Multimedia research incorporates elements of Human–computer interaction and Presentation.
His study on Human–computer interaction also encompasses disciplines like
- Affect together with Cognitive psychology,
- Embodied cognition which is related to area like Gesture.
He most often published in these fields:
- Artificial intelligence (40.72%)
- Natural language processing (22.57%)
- Information retrieval (22.36%)
What were the highlights of his more recent work (between 2009-2015)?
- Artificial intelligence (40.72%)
- Natural language processing (22.57%)
- Information retrieval (22.36%)
In recent papers he was focusing on the following fields of study:
Mitsuru Ishizuka focuses on Artificial intelligence, Natural language processing, Information retrieval, World Wide Web and Relationship extraction.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Context, Machine learning, Relation and Pattern recognition.
His Natural language processing study incorporates themes from Word and Principle of compositionality.
Mitsuru Ishizuka has researched World Wide Web in several fields, including User modeling and Human–computer interaction.
Mitsuru Ishizuka has included themes like Semi-supervised learning, Feature extraction and Document clustering in his Relationship extraction study.
The concepts of his Semantic search study are interwoven with issues in Semantic computing and Semantic similarity.
Between 2009 and 2015, his most popular works were:
- HILDA: A Discourse Parser Using Support Vector Machine Classification (200 citations)
- A Web Search Engine-Based Approach to Measure Semantic Similarity between Words (174 citations)
- SentiFul: A Lexicon for Sentiment Analysis (130 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Machine learning
Mitsuru Ishizuka mostly deals with Artificial intelligence, Natural language processing, Relationship extraction, Information retrieval and Sentence.
His research in Artificial intelligence is mostly concerned with Classifier.
He interconnects Discourse relation and Principle of compositionality in the investigation of issues within Natural language processing.
His Relationship extraction research is multidisciplinary, incorporating elements of Web mining, GRASP and Pattern recognition.
He studies Relational database which is a part of Information retrieval.
His work in Sentence covers topics such as Phrase which are related to areas like Complement and Interpretation.
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