|
|
|
|
| LEADER |
00000cam a2200000 a 4500 |
| 001 |
on1225069109 |
| 003 |
OCoLC |
| 005 |
20240808213014.0 |
| 006 |
m o d |
| 007 |
cr |n||||||||| |
| 008 |
201202s2020 sz o 101 0 eng d |
| 040 |
|
|
|a YDX
|b eng
|e pn
|c YDX
|d GW5XE
|d EBLCP
|d UKQUB
|d OCLCO
|d OCLCF
|d LEATE
|d SFB
|d DKU
|d OCL
|d OCLCO
|d OCLCQ
|d COM
|d OCLCO
|d OCLCQ
|d OCLCO
|d OCLCL
|
| 019 |
|
|
|a 1225198797
|a 1225548415
|a 1237465186
|a 1241727252
|a 1264794654
|
| 020 |
|
|
|a 9783030630072
|q (electronic bk.)
|
| 020 |
|
|
|a 3030630072
|q (electronic bk.)
|
| 020 |
|
|
|z 3030630064
|
| 020 |
|
|
|z 9783030630065
|
| 024 |
7 |
|
|a 10.1007/978-3-030-63007-2
|2 doi
|
| 035 |
|
|
|a (OCoLC)1225069109
|z (OCoLC)1225198797
|z (OCoLC)1225548415
|z (OCoLC)1237465186
|z (OCoLC)1241727252
|z (OCoLC)1264794654
|
| 050 |
|
4 |
|a QA76.76.E95
|b I33 2020eb
|
| 072 |
|
7 |
|a COM004000
|2 bisacsh
|
| 072 |
|
7 |
|a UYQ
|2 bicssc
|
| 072 |
|
7 |
|a UYQ
|2 thema
|
| 049 |
|
|
|a HCDD
|
| 111 |
2 |
|
|a ICCCI (Conference)
|n (12th :
|d 2020 :
|c Online)
|
| 245 |
1 |
0 |
|a Computational collective intelligence :
|b 12th international conference, ICCCI 2020 Da Nang, Vietnam, November 30-December 3, 2020 proceedings /
|c Ngoc Thanh Nguyen, Bao Hung Hoang, Cong Phap Huynh, Dosam Hwang, Bogdan Trawiński, Gottfried Vossen (eds.).
|
| 246 |
3 |
|
|a ICCCI 2020
|
| 260 |
|
|
|a Cham, Switzerland :
|b Springer,
|c 2020.
|
| 300 |
|
|
|a 1 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
|
| 347 |
|
|
|b PDF
|
| 490 |
1 |
|
|a Lecture Notes in Computer Science ;
|v 12496
|
| 490 |
1 |
|
|a Lecture notes in artificial intelligence
|
| 490 |
1 |
|
|a LNCS sublibrary, SL 7, Artificial intelligence
|
| 500 |
|
|
|a International conference proceedings.
|
| 500 |
|
|
|a "The conference was held virtually due to the COVID-19 pandemic."
|
| 520 |
|
|
|a This volume constitutes the refereed proceedings of the 12th International Conference on Computational Collective Intelligence, ICCCI 2020, held in Da Nang, Vietnam, in November 2020.* The 70 full papers presented were carefully reviewed and selected from 314 submissions. The papers are grouped in topical sections on: knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; applications of collective intelligence; data mining methods and applications; machine learning methods; deep learning and applications for industry 4.0; computer vision techniques; biosensors and biometric techniques; innovations in intelligent systems; natural language processing; low resource languages processing; computational collective intelligence and natural language processing; computational intelligence for multimedia understanding; and intelligent processing of multimedia in web systems. *The conference was held virtually due to the COVID-19 pandemic.
|
| 500 |
|
|
|a Includes author index.
|
| 588 |
0 |
|
|a Online resource; title from PDF title page (SpringerLink, viewed February 3, 2021).
|
| 505 |
0 |
|
|a Intro -- Preface -- Organization -- Contents -- Knowledge Engineering and Semantic Web -- Towards a Holistic Schema Matching Approach Designed for Large-Scale Schemas -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 The HMO Approach -- 4.1 Overlaps and Distinctions Generator -- 4.2 Schema Overlaps Matcher -- 4.3 Distinct Elements Matcher -- 5 Experimental Results -- 5.1 Experimental Settings -- 5.2 Results and Discussion -- 6 Conclusion and Future Work -- References -- Overcoming Local Optima for Determining 2-Optimality Consensus for Collectives -- 1 Introduction
|
| 505 |
8 |
|
|a 2 Related Work -- 3 Basic Notions -- 4 Proposed Approach -- 5 Experiments and Evaluation -- 5.1 Consensus Quality -- 5.2 Running Time -- 6 Conclusions -- References -- Fundamentals of Generalized and Extended Graph-Based Structural Modeling -- 1 Introduction -- 2 Formal Definitions -- 3 Extended Graph Generalization Abstract Syntax -- 4 Extended Graph Generalization Features -- 5 Extended Graph Generalization Semantics -- 6 Extended Graph Generalization Concrete Syntax -- 6.1 Extended Graph Generalization Diagram Example -- 7 A Social Network Model Example Expressed in the EGG Categories
|
| 505 |
8 |
|
|a 8 Conclusions -- References -- Social Networks and Recommender Systems -- Topic Diffusion Prediction on Bibliographic Network: New Approach with Combination Between External and Intrinsic Factors -- 1 Introduction -- 2 Preliminaries -- 2.1 Meta-Path -- 3 Proposed Approach -- 3.1 Supervised Learning for Topic Diffusion on Bibliographic Network -- 3.2 Activation Probability Feature -- 3.3 Author's Interest Feature -- 4 Experiments and Results -- 4.1 Experiments -- 4.2 Results -- 5 Conclusion and Future Work -- References
|
| 505 |
8 |
|
|a Detecting the Degree of Risk in Online Market Based on Satisfaction of Twitter Users -- 1 Introduction -- 2 Related Works -- 3 Research Problem -- 3.1 Definition of Tweet and Types of Tweet Sentiments -- 3.2 Definition of Different Types of User Satisfaction -- 3.3 Definition of Different Degrees of Risk -- 3.4 Research Question -- 4 Proposed Method -- 4.1 Feature Extraction -- 4.2 Tweet Sentiment Analysis -- 4.3 Determining the User Satisfaction, Dissatisfaction, and Hesitation -- 4.4 Calculating the Degree of Risk -- 5 Experiment -- 5.1 Data Acquisition -- 5.2 Evaluation Results
|
| 505 |
8 |
|
|a 5.3 Results and Discussion -- 6 Conclusion and Future Work -- References -- Method of Detecting Bots on Social Media. A Literature Review -- 1 Introduction and Background -- 2 Type of Bots -- 3 Method of Detecting Social Bots -- 3.1 Social Media Giant Model -- 3.2 Experts-Approach -- 3.3 Collective Intelligence-Approach -- 3.4 Machine Learning Model -- 3.5 Hybrid Method -- 3.6 Graphical Modeling to Detect Bots -- 3.7 Behavioral Based-Model -- 4 Discussion and Open Challenges -- 5 Conclusions and Future Directions -- References
|
| 650 |
|
0 |
|a Expert systems (Computer science)
|v Congresses.
|
| 650 |
|
0 |
|a Intelligent agents (Computer software)
|v Congresses.
|
| 650 |
|
0 |
|a Artificial intelligence
|v Congresses.
|
| 650 |
|
0 |
|a Semantic Web
|v Congresses.
|
| 650 |
|
0 |
|a Human-computer interaction
|v Congresses.
|
| 650 |
|
7 |
|a Semantic Web
|2 fast
|
| 650 |
|
7 |
|a Intelligent agents (Computer software)
|2 fast
|
| 650 |
|
7 |
|a Human-computer interaction
|2 fast
|
| 650 |
|
7 |
|a Expert systems (Computer science)
|2 fast
|
| 650 |
|
7 |
|a Application software
|2 fast
|
| 650 |
|
7 |
|a Artificial intelligence
|2 fast
|
| 650 |
|
7 |
|a Computer networks
|2 fast
|
| 650 |
|
7 |
|a Computers
|2 fast
|
| 650 |
|
7 |
|a Optical data processing
|2 fast
|
| 655 |
|
7 |
|a proceedings (reports)
|2 aat
|
| 655 |
|
7 |
|a Conference papers and proceedings
|2 fast
|
| 655 |
|
7 |
|a Conference papers and proceedings.
|2 lcgft
|
| 655 |
|
7 |
|a Actes de congrès.
|2 rvmgf
|
| 700 |
1 |
|
|a Nguyen, Ngoc Thanh
|c (Computer scientist)
|1 https://id.oclc.org/worldcat/entity/E39PBJyrXJQyVj9XYCk9Q4X68C
|
| 700 |
1 |
|
|a Hoang, Bao Hung.
|
| 700 |
1 |
|
|a Huynh, Cong Phap.
|
| 700 |
1 |
|
|a Hwang, Dosam.
|
| 700 |
1 |
|
|a Trawiński, Bogdan.
|
| 700 |
1 |
|
|a Vossen, Gottfried.
|
| 758 |
|
|
|i has work:
|a Computational collective intelligence (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCFrpKMrrBH3jtvgjKyqwvd
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a ICCCI (Conference) (12th : 2020 : Online).
|t Computational collective intelligence.
|d Cham, Switzerland : Springer, 2020
|z 3030630064
|z 9783030630065
|w (OCoLC)1198979289
|
| 830 |
|
0 |
|a Lecture notes in computer science ;
|v 12496.
|
| 830 |
|
0 |
|a Lecture notes in computer science.
|p Lecture notes in artificial intelligence.
|
| 830 |
|
0 |
|a LNCS sublibrary.
|n SL 7,
|p Artificial intelligence.
|
| 856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-63007-2
|y Click for online access
|
| 903 |
|
|
|a SPRING-COMP2020
|
| 994 |
|
|
|a 92
|b HCD
|