IEEE International Conference on Electro-Information Technology , EIT 2013 2013
DOI: 10.1109/eit.2013.6857939
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A concept of semantics extraction from web data by induction of fuzzy ontologies

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Cited by 13 publications
(25 citation statements)
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“…Engelbart [7] previously proposed a mechanism to enhance human reasoning in 1962 through the assistance of computers. This idea is captured by the concept of the intelligence amplification loop, which proposes that both humans and computers learn through mutual interaction [19,37]. This process is characterized by emergence (i.e., the phenomena whereby new properties emerge unplanned from the interaction of a system's components) [9].…”
Section: Cognitive Computingmentioning
confidence: 99%
“…Engelbart [7] previously proposed a mechanism to enhance human reasoning in 1962 through the assistance of computers. This idea is captured by the concept of the intelligence amplification loop, which proposes that both humans and computers learn through mutual interaction [19,37]. This process is characterized by emergence (i.e., the phenomena whereby new properties emerge unplanned from the interaction of a system's components) [9].…”
Section: Cognitive Computingmentioning
confidence: 99%
“…The use of fuzzy sets allows organically grooming gradual knowledge structures from existing Web content. The lower a membership degree for belonging to a topic, the farther away it should be represented within the Topic Map [23,24]. A fuzzy membership degree thereby expresses the Social Web's different knowledge granularity that is automatically captured by the framework.…”
Section: Motivationmentioning
confidence: 99%
“…To interact with live data, the tagspace needs to be continually updated. As a result, the introduced approximate plotting algorithm is able to provide a good perspective on moving data [23,24].…”
mentioning
confidence: 98%
“…Similarly, there is an interesting paper, [13], thoroughly analyzing the possibilities of mining fuzzy association rules in texts; that track could be followed and applied on step further to finding fuzzy associations between textual information A Retrospective Assessment of Fuzzy Logic Applications in Voice Communications and Speech Analytics 869 and prosody and emotions in speech. Another remarkable approach to analytics based on FL but not related to speech is constituted by a series of papers [30], [31] that apply fuzzy data analysis and inductive fuzzy classification using a normalization of the likelihood ratio to metadata and for knowledge discovery. Surprisingly, there are few reports on research on FL applied to speech analytics related to emotions.…”
Section: Fl In Speech Analytics -A Surprising Low Developmentmentioning
confidence: 99%