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001451962 001__ 1451962
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001451962 019__ $$a1355267348
001451962 020__ $$a9783031235047$$q(electronic bk.)
001451962 020__ $$a3031235045$$q(electronic bk.)
001451962 020__ $$z3031235037
001451962 020__ $$z9783031235030
001451962 0247_ $$a10.1007/978-3-031-23504-7$$2doi
001451962 035__ $$aSP(OCoLC)1356005655
001451962 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX
001451962 049__ $$aISEA
001451962 050_4 $$aQ334
001451962 08204 $$a006.3$$223/eng/20230104
001451962 1112_ $$aAIMS (Conference : Artificial Intelligence and Mobile Services)$$n(11th :$$d2022 :$$cHonolulu, HI)
001451962 24510 $$aArtificial intelligence and mobile services -- AIMS 2022 :$$b11th International Conference, held as part of the Services Conference Federation, SCF 2022, Honolulu, HI, USA, December 10-14, 2022, Proceedings /$$cXiuqin Pan, Ting Jin, Liang-Jie Zhang (eds.).
001451962 2463_ $$aAIMS 2022
001451962 260__ $$aCham :$$bSpringer,$$c2022.
001451962 300__ $$a1 online resource (146 p.).
001451962 4901_ $$aLecture notes in computer science ;$$v13729
001451962 500__ $$aIndicator-Specific Recurrent Neural Networks with Co-teaching for Stock Trend Prediction
001451962 500__ $$aIncludes author index.
001451962 504__ $$aReferences -- Chinese Text Classification Using BERT and Flat-Lattice Transformer -- 1 Introduction -- 2 Related Work -- 2.1 Traditional and Embedding-Based Text Classification -- 2.2 Neural Network Text Classification -- 2.3 Chinese Text Classification -- 2.4 Transformer Related Theory -- 3 Approaches -- 3.1 Converting Lattice into Flat Structure -- 3.2 Relative Position Encoding of Spans -- 3.3 Classifier and Optimization -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Overall Performance -- 5 Conclusion -- References
001451962 5050_ $$aIntro -- Preface -- Organization -- Services Society -- Services Conference Federation (SCF) -- Contents -- Research Track -- Push-Based Forwarding Scheme Using Fuzzy Logic to Mitigate the Broadcasting Storm Effect in VNDN -- 1 Introduction -- 2 Vehicular Named Data Networking (VNDN) -- 2.1 Content Store (CS) -- 2.2 Pending Interest Table (PIT) -- 2.3 Forwarding Information Base (FIB) -- 2.4 Consumer Vehicle -- 2.5 Producer Vehicle -- 3 Push-Based Data Forwarding in VNDN -- 4 Proposed Push-Based Data Forwarding Scheme with Fuzzy Logic -- 4.1 K-Means Clustering
001451962 5058_ $$a4.2 Selection of Cluster Head (CH) Using Fuzzy Logic -- 4.3 Proposed Data Packet Format -- 4.4 Proposed Scheme for Producer -- 4.5 Proposed Scheme for Consumer -- 4.6 Critical Data Forwarding Procedure by the Proposed Scheme -- 5 Simulation Environment and Results -- 6 Conclusion -- References -- DCRNNX: Dual-Channel Recurrent Neural Network with Xgboost for Emotion Identification Using Nonspeech Vocalizations -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Dual-Channel Neural Network Model -- 3.2 Introducing Attention Mechanism in Two-Channel Model -- 3.3 XGBoost Classifier
001451962 5058_ $$a3.4 Model Fusion Using L2 Norm -- 4 Experiments -- 4.1 Datasets Used -- 4.2 Experimental Setup -- 4.3 Experimental Results -- 4.4 Introduce Attention Mechanism -- 4.5 Data Augmentation -- 5 Conclusion -- References -- STaR: Knowledge Graph Embedding by Scaling, Translation and Rotation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Background Knowledge -- 3.2 The Proposed STaR Model -- 3.3 Discussions -- 4 Experiments -- 4.1 Experiments Settings -- 4.2 Main Results -- 5 Analysis -- 5.1 Further Comparison with ComplEx -- 5.2 Imbalance Ratio Among KGs
001451962 5058_ $$a5.3 Improvements on WN18RR Come from Modeling Non-commutativity Pattern -- 6 Conclusion -- References -- Application Track -- Frequently Asked Question Pair Generation for Rule and Regulation Document -- 1 Introduction -- 2 Related Work -- 2.1 QA Pair Generation -- 2.2 FAQ Pair Generation -- 3 Data Collection and Analysis -- 3.1 Data Collection -- 3.2 Data Analysis -- 4 Methodology -- 4.1 Rule-Based FAQ Pair Generation -- 4.2 Pipeline Framework -- 5 Experiment -- 5.1 Experiment Setting -- 5.2 Evaluation Metrics -- 5.3 Analysis Experiment -- 5.4 Human Evaluation -- 5.5 Case Study -- 6 Conclusion
001451962 506__ $$aAccess limited to authorized users.
001451962 520__ $$aThis book constitutes the proceedings of the 11th International Conference on Artificial Intelligence and Mobile Services, AIMS 2022, held as Part of the Services Conference Federation, SCF 2022, held in Honolulu, HI, USA, in December 2022. The 10 full papers presented in this volume were carefully reviewed and selected from 22 submissions. The International Conference on AI & Mobile Services (AIMS 2022) aims at providing an international forum that is dedicated to exploring different aspects of AI (from technologies to approaches and algorithms) and mobile services (from business management to computing systems, algorithms, and applications) to promoting technological innovations in research and development of mobile services, including, but not limited to, wireless & sensor networks, mobile & wearable computing, mobile enterprise & eCommerce, ubiquitous collaborative & social services, machine-to-machine & Internet-of-things clouds, cyber-physical integration, and big data analytics for mobility-enabled services.
001451962 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 4, 2023).
001451962 650_0 $$aArtificial intelligence$$vCongresses.
001451962 650_0 $$aMobile computing$$vCongresses.
001451962 655_0 $$aElectronic books.
001451962 7001_ $$aPan, Xiuqin.
001451962 7001_ $$aJin, Ting.
001451962 7001_ $$aZhang, Liang-Jie.
001451962 7102_ $$aServices Conference Federation$$d(2020 :$$cHonolulu, HI)
001451962 77608 $$iPrint version:$$aPan, Xiuqin$$tArtificial Intelligence and Mobile Services - AIMS 2022$$dCham : Springer International Publishing AG,c2023$$z9783031235030
001451962 830_0 $$aLecture notes in computer science ;$$v13729.
001451962 852__ $$bebk
001451962 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-23504-7$$zOnline Access$$91397441.1
001451962 909CO $$ooai:library.usi.edu:1451962$$pGLOBAL_SET
001451962 980__ $$aBIB
001451962 980__ $$aEBOOK
001451962 982__ $$aEbook
001451962 983__ $$aOnline
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