國立虎尾科技大學 |

Data Visualization and Knowledge Engineering = Spotting Data Points with Artificial Intelligence /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data Visualization and Knowledge Engineering/ edited by Jude Hemanth, Madhulika Bhatia, Oana Geman.
其他題名:	Spotting Data Points with Artificial Intelligence /
其他作者:	Hemanth, Jude.
面頁冊數:	VI, 319 p. 213 illus., 92 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-25797-2
ISBN:	9783030257972

Data Visualization and Knowledge Engineering = Spotting Data Points with Artificial Intelligence /
Data Visualization and Knowledge EngineeringSpotting Data Points with Artificial Intelligence /[electronic resource] :edited by Jude Hemanth, Madhulika Bhatia, Oana Geman. - 1st ed. 2020. - VI, 319 p. 213 illus., 92 illus. in color.online resource. - Lecture Notes on Data Engineering and Communications Technologies,322367-4512 ;. - Lecture Notes on Data Engineering and Communications Technologies,3.

Cross Projects Defect Prediction Modeling -- Recommendation Systems for Interactive Multimedia Entertainment -- Image Collection Summarization: Past, Present and Future -- Semantic Web and Data Visualization -- Analysis and Visualization of User Navigations on Web -- Research Trends for Named Entity Recognition in Hindi Language -- Data Visualization Techniques, Model and Taxonomy -- Prevalence of Visualization Techniques in Data Mining -- Relevant Subsection Retrieval for Law Domain Question Answer System -- Brain Tumor Segmentation Using OTSU Embedded Adaptive Particle Swarm Optimization Method and Convolutional Neural Network -- Challenges and Responses Towards Sustainable Future through Machine Learning and Deep learning -- A Deep Dive into Supervised Extractive and Abstractive Summarization from Text.

This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge. Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns. A variety of scalable data visualization techniques are required to deal with constantly increasing volume of data in different formats. Knowledge engineering deals with the simulation of the exchange of ideas and the development of smart information systems in which reasoning and knowledge play an important role. Presenting research in areas like data visualization and knowledge engineering, this book is a valuable resource for students, scholars and researchers in the field. Each chapter is self-contained and offers an in-depth analysis of real-world applications. It discusses topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and visualization; perception and cognition in visualization; visualization taxonomies and models; abstract data visualization; information and graph visualization; knowledge engineering; human–machine cooperation; metamodeling; natural language processing; architectures of database, expert and knowledge-based systems; knowledge acquisition methods; applications, case studies and management issues: data administration issues and knowledge; tools for specifying and developing data and knowledge bases using tools based on communication aspects involved in implementing, designing and using KBSs in cyberspace; Semantic Web.

ISBN: 9783030257972

Standard No.: 10.1007/978-3-030-25797-2doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Data Visualization and Knowledge Engineering = Spotting Data Points with Artificial Intelligence /
LDR:04378nam a22003975i 4500 001 1018087
003 DE-He213
005 20200702005414.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030257972 $9 978-3-030-25797-2
024 7 $a 10.1007/978-3-030-25797-2 $2 doi
035 $a 978-3-030-25797-2
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Data Visualization and Knowledge Engineering $h [electronic resource] : $b Spotting Data Points with Artificial Intelligence / $c edited by Jude Hemanth, Madhulika Bhatia, Oana Geman.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a VI, 319 p. 213 illus., 92 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Lecture Notes on Data Engineering and Communications Technologies, $x 2367-4512 ; $v 32
505 0 $a Cross Projects Defect Prediction Modeling -- Recommendation Systems for Interactive Multimedia Entertainment -- Image Collection Summarization: Past, Present and Future -- Semantic Web and Data Visualization -- Analysis and Visualization of User Navigations on Web -- Research Trends for Named Entity Recognition in Hindi Language -- Data Visualization Techniques, Model and Taxonomy -- Prevalence of Visualization Techniques in Data Mining -- Relevant Subsection Retrieval for Law Domain Question Answer System -- Brain Tumor Segmentation Using OTSU Embedded Adaptive Particle Swarm Optimization Method and Convolutional Neural Network -- Challenges and Responses Towards Sustainable Future through Machine Learning and Deep learning -- A Deep Dive into Supervised Extractive and Abstractive Summarization from Text.
520 $a This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge. Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns. A variety of scalable data visualization techniques are required to deal with constantly increasing volume of data in different formats. Knowledge engineering deals with the simulation of the exchange of ideas and the development of smart information systems in which reasoning and knowledge play an important role. Presenting research in areas like data visualization and knowledge engineering, this book is a valuable resource for students, scholars and researchers in the field. Each chapter is self-contained and offers an in-depth analysis of real-world applications. It discusses topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and visualization; perception and cognition in visualization; visualization taxonomies and models; abstract data visualization; information and graph visualization; knowledge engineering; human–machine cooperation; metamodeling; natural language processing; architectures of database, expert and knowledge-based systems; knowledge acquisition methods; applications, case studies and management issues: data administration issues and knowledge; tools for specifying and developing data and knowledge bases using tools based on communication aspects involved in implementing, designing and using KBSs in cyberspace; Semantic Web.
650 0 $a Computational intelligence. $3 568984
650 0 $a Artificial intelligence. $3 559380
650 0 $a Data mining. $3 528622
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Data Mining and Knowledge Discovery. $3 677765
700 1 $a Hemanth, Jude. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1229121
700 1 $a Bhatia, Madhulika. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1313006
700 1 $a Geman, Oana. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1313007
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030257965
776 0 8 $i Printed edition: $z 9783030257989
830 0 $a Lecture Notes on Data Engineering and Communications Technologies, $x 2367-4512 ; $v 3 $3 1279482
856 4 0 $u https://doi.org/10.1007/978-3-030-25797-2
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)