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001483973 001__ 1483973
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001483973 019__ $$a1407346895
001483973 020__ $$a9789819978557$$q(electronic bk.)
001483973 020__ $$a9819978556$$q(electronic bk.)
001483973 020__ $$z9819978548
001483973 020__ $$z9789819978540
001483973 0247_ $$a10.1007/978-981-99-7855-7$$2doi
001483973 035__ $$aSP(OCoLC)1409029289
001483973 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dOCLCO$$dYDX$$dOCLCO
001483973 049__ $$aISEA
001483973 050_4 $$aQ334$$b.K569 2023
001483973 08204 $$a006.3/31$$223/eng/20231113
001483973 1112_ $$aPacific Rim Knowledge Acquisition Workshop$$n(19th :$$d2023 :$$cJakarta, Indonesia)
001483973 24510 $$aKnowledge management and acquisition for intelligent systems :$$b19th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2023, Jakarta, Indonesia, November 15-16, 2023, Proceedings /$$cShiqing Wu, Wenli Yang, Muhammad Bilal Amin, Byeong-Ho Kang, Guandong Xu, editors.
001483973 2463_ $$aPKAW 2023
001483973 260__ $$aSingapore :$$bSpringer,$$c2023.
001483973 300__ $$a1 online resource (156 p.).
001483973 4901_ $$aLecture notes in artificial intelligence
001483973 4901_ $$aLecture Notes in Computer Science ;$$v14317
001483973 4901_ $$aLNCS sublibrary, SL 7, Artificial intelligence
001483973 500__ $$a4.3 Influence Gap
001483973 500__ $$aIncludes author index.
001483973 5050_ $$aIntro -- Preface -- Organization -- Contents -- Predicting Peak Demand Days for Asthma-Related Emergency Hospitalisations: A Machine Learning Approach -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Collection from Diverse Sources -- 3.2 Data Preparation -- 3.3 Data Analysis and Feature Selection -- 3.4 Prediction Model -- 4 Results -- 5 Conclusion -- References -- Discovering Maximal High Utility Co-location Patterns from Spatial Data -- 1 Introduction -- 2 Maximal High Utility Co-location Patterns -- 3 The Proposed Mining Algorithm -- 3.1 Collecting Participating Instances
001483973 5058_ $$a3.2 Calculating Utility Participating Indexes -- 4 Experimental Results -- 4.1 Data Sets -- 4.2 Performance on Reducing Number of HUCPs -- 4.3 Performance on Different User-Specified Interesting Thresholds -- 4.4 Performance on Different Distance Thresholds -- 4.5 Performance on Different Numbers of Instances -- 5 Conclusion -- References -- Exploring the Potential of Image Overlay in Self-supervised Learning: A Study on SimSiam Networks and Strategies for Preventing Model Collapse -- 1 Introduction -- 2 Related Work -- 2.1 Noteworthy Models -- 2.2 Mitigating Dimensional Collapse
001483973 5058_ $$a3 Research Design -- 3.1 Supervised Learning Design -- 3.2 SSL Experiment Design -- 3.3 Overlay and Extend Adjustments -- 4 Findings and Discussions -- 4.1 Supervised Benchmark -- 4.2 Collapse in SimSiam -- 4.3 Overlay Potential -- 5 Conclusion -- References -- BoCB: Performance Benchmarking by Analysing Impacts of Cloud Platforms on Consortium Blockchain -- 1 Introduction -- 2 Related Work -- 3 Benchmarking Methodology -- 3.1 Experiment Framework and Performance Modelling -- 3.2 Applications and Scenarios Design -- 3.3 Configuration and Workload -- 4 Results and Analysis
001483973 5058_ $$a4.1 Horizontal Comparison -- 4.2 Vertical Comparison -- 5 Conclusion and Future Work -- References -- Automated Cattle Behavior Classification Using Wearable Sensors and Machine Learning Approach -- 1 Introduction -- 1.1 Animals and Data Collection -- 1.2 Dataset -- 1.3 Machine Learning Algorithm and Evaluation -- 2 Classification Results -- 3 Conclusion -- References -- LexiFusedNet: A Unified Approach for Imbalanced Short-Text Classification Using Lexicon-Based Feature Extraction, Transfer Learning and One Class Classifiers -- 1 Introduction -- 2 Related Work -- 3 Fully Deep LexiFusedNet
001483973 5058_ $$a3.1 Building Supervised Pre-trained Models -- 3.2 Building Self-Taught Fine-Tuned One-Class Model -- 4 Experimental Setup -- 4.1 Models -- 4.2 Dataset -- 4.3 Lexicon -- 4.4 Performance Metric -- 5 Result -- 6 Discussion -- 7 Conclusion -- References -- Information Gerrymandering in Elections -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 3.1 Information Gerrymandering from Literature -- 4 Effective Influence Assortment in General Scenarios -- 4.1 Influence Assortment on the Node Level -- 4.2 Considering the Echo Chamber Factor for Influence Assortment on the Party Level
001483973 506__ $$aAccess limited to authorized users.
001483973 520__ $$aThis book constitutes the refereed proceedings of the 19th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2023, held in conjunction with the 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2023), in November 2023, in Jakarta, Indonesia. The 9 full papers and 2 short papers included in this volume were carefully reviewed and selected from 28 initial submissions. They are organized in the topical section such as machine learning, natural language processing, and intelligent systems.
001483973 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed November 13, 2023).
001483973 650_6 $$aIntelligence artificielle$$vCongrès.
001483973 650_6 $$aExploration de données (Informatique)$$vCongrès.
001483973 650_6 $$aGestion des connaissances$$vCongrès.
001483973 650_0 $$aArtificial intelligence$$vCongresses.$$xMedical applications$$0(DLC)sh 88003000
001483973 650_0 $$aData mining$$vCongresses.$$vCongresses$$0(DLC)sh2008102035
001483973 650_0 $$aKnowledge management$$vCongresses.$$vCongresses$$0(DLC)sh2008106316
001483973 655_0 $$aElectronic books.
001483973 7001_ $$aWu, Shiqing.
001483973 7001_ $$aYang, Wenli.
001483973 7001_ $$aAmin, Muhammad Bilal.
001483973 7001_ $$aKang, Byeong-Ho.
001483973 7001_ $$aXu, Guandong.
001483973 77608 $$iPrint version:$$aWu, Shiqing$$tKnowledge Management and Acquisition for Intelligent Systems$$dSingapore : Springer Singapore Pte. Limited,c2023$$z9789819978540
001483973 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001483973 830_0 $$aLecture notes in computer science ;$$v14317.
001483973 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001483973 852__ $$bebk
001483973 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-7855-7$$zOnline Access$$91397441.1
001483973 909CO $$ooai:library.usi.edu:1483973$$pGLOBAL_SET
001483973 980__ $$aBIB
001483973 980__ $$aEBOOK
001483973 982__ $$aEbook
001483973 983__ $$aOnline
001483973 994__ $$a92$$bISE