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Levels of knowledge for object extraction
Machine Vision and Applications, 1991A paradigm for image interpretation and object extraction that deals explicitly with the levels of abstraction of such processes is described. The central new feature of this paradigm is two intermediate-level processes that deal with construction of symbolic image tokens and with symbolic descriptions of quantities.
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2016
This article presented an anomaly detection method based on techniques of knowledge extraction from data, which can be fully applied to detect anomalous working conditions and prevent unexpected faults and shut downs of subsystems of energy production and fluid process plants such as in the LNG transport and production industry.
Brighenti, Chiara +3 more
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This article presented an anomaly detection method based on techniques of knowledge extraction from data, which can be fully applied to detect anomalous working conditions and prevent unexpected faults and shut downs of subsystems of energy production and fluid process plants such as in the LNG transport and production industry.
Brighenti, Chiara +3 more
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Multi-knowledge Extraction and Application
2003Rough set theory provides approaches to the finding a reduct (informally, an identifying set of attributes) from a decision system or a training set. In this paper, an algorithm for finding multiple reducts is developed. The algorithm has been used to find the multi-reducts in data sets from UCI Machine Learning Repository.
Qingxiang Wu, David A. Bell
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Knowledge extraction from fictional texts
2022Wissensextraktion ist ein Schlüsselaufgabe bei der Verarbeitung natürlicher Sprache, und umfasst viele Unteraufgaben, wie Taxonomiekonstruktion, Entitätserkennung und Typisierung, Relationsextraktion, Wissenskanonikalisierung, etc. Durch den Aufbau von strukturiertem Wissen (z.B.
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Making Knowledge Extraction and Reasoning Closer
2000The paper shows how a logic-based database language can support the various steps of the KDD process by providing a high degree of expressiveness, and the separation of concerns between the specification level and the mapping to the underlying databases and data mining tools.
Giannotti F, Manco G
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Interest Propagation for Knowledge Extraction and Representation
2013Due to the increasing number of available biomedical data repositories, providing a comprehensive and intuitive access to information is still a demanding task for Information Retrieval systems. In this work we present an interactive data exploration system that retrieves relevant information by propagating the user's interest within a network.
Francesca Mulas +3 more
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Extractive Knowledge Distillation
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022openaire +2 more sources
Knowledge Extraction from Reinforcement Learning
IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 2002This paper deals with knowledge extraction from reinforcement learners. It addresses two approaches towards knowledge extraction: the extraction of explicit, symbolic rules front neural reinforcement learners; and the extraction of complete plans from such learners.
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Biological Knowledge Extraction
2009Text Mining is the process of extracting [novel] interesting and non-trivial information and knowledge from unstructured text (Google™ search result for “define: text mining”). Information retrieval, natural language processing, information extraction, and text mining provide methodologies to shift the burden of tracing and relating data contained in ...
Florian Leitner +2 more
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Supersemantics for Knowledge Extraction.
2015In several areas of science, the publication rate exceeds the human reading speed. Text mining tackles this problem by automatically extracting relevant knowledge from scientific articles. This thesis introduces Supersemantics as an approach to integrate different linguistic and other adjacent fields.
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