His primary areas of investigation include Artificial intelligence, Natural language processing, Word, Speech recognition and Convolutional neural network. His studies in Artificial intelligence integrate themes in fields like Context, Machine learning and Pattern recognition. His Lexicon study, which is part of a larger body of work in Natural language processing, is frequently linked to Field, bridging the gap between disciplines.
His Word research incorporates elements of Syntax, Space and Similarity. His Convolutional neural network research integrates issues from Textual entailment, Representation and Selection. His Information science research extends to the thematically linked field of Information retrieval.
Artificial intelligence, Natural language processing, Word, Language model and Information retrieval are his primary areas of study. His Artificial intelligence study combines topics in areas such as Context, Machine learning and Pattern recognition. His Natural language processing research is multidisciplinary, incorporating elements of Knowledge base, Speech recognition, Selection and German.
His Word research incorporates elements of Space, Morpheme, Similarity, Deep learning and Semantics. The Language model study combines topics in areas such as Training set and Generative grammar. His research related to Human–computer information retrieval, Relevance, Search engine, Query expansion and Vector space model might be considered part of Information retrieval.
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Language model, Word and Sentence. In his work, Morphology and Syntax is strongly intertwined with Morphology, which is a subfield of Artificial intelligence. His Natural language processing study combines topics in areas such as Context, Vocabulary, Inference and Benchmark.
The concepts of his Language model study are interwoven with issues in Machine learning, Generative grammar and Cognitive science. His Word study incorporates themes from German, Space, Lexicon, Interpretability and Bilingual dictionary. He studied Normalization and Biomedical text mining that intersect with Relevance.
Hinrich Schütze mostly deals with Artificial intelligence, Natural language processing, Language model, Training set and Word. Artificial intelligence and Component are two areas of study in which he engages in interdisciplinary work. His research in Natural language processing intersects with topics in Context and Embedding.
His Language model research includes elements of Cognitive psychology, Negation and Priming. His work deals with themes such as Natural language inference, Word order, Margin, Natural language and Shot, which intersect with Training set. In the subject of general Word, his work in SemEval is often linked to Divergence, thereby combining diverse domains of 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.
Introduction to Information Retrieval
Christopher D. Manning;Prabhakar Raghavan;Hinrich Schütze.
Automatic word sense discrimination
Computational Linguistics (1998)
Dimensions of meaning
conference on high performance computing (supercomputing) (1992)
A comparison of classifiers and document representations for the routing problem
Hinrich Schütze;David A. Hull;Jan O. Pedersen.
international acm sigir conference on research and development in information retrieval (1995)
ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs
Wenpeng Yin;Hinrich Schütze;Bing Xiang;Bowen Zhou.
Transactions of the Association for Computational Linguistics (2016)
Comparative Study of CNN and RNN for Natural Language Processing
Wenpeng Yin;Katharina Kann;Mo Yu;Hinrich Schütze.
arXiv: Computation and Language (2017)
Automatic Detection of Text Genre
Brett Kessler;Geoffrey Nunberg;Hinrich Schutze.
meeting of the association for computational linguistics (1997)
A cooccurrence-based thesaurus and two applications to information retrieval
Hinrich Schütze;Jan O. Pedersen.
Information Processing and Management (1997)
neural information processing systems (1992)
Projections for efficient document clustering
Hinrich Schütze;Craig Silverstein.
international acm sigir conference on research and development in information retrieval (1997)
Profile was last updated on December 6th, 2021.
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