001451802 000__ 05930cam\a2200673\i\4500
001451802 001__ 1451802
001451802 003__ OCoLC
001451802 005__ 20230310004718.0
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001451802 008__ 221209s2022\\\\sz\a\\\\o\\\\\101\0\eng\d
001451802 019__ $$a1354205444
001451802 020__ $$a9783031203091$$q(electronic bk.)
001451802 020__ $$a3031203097$$q(electronic bk.)
001451802 020__ $$z9783031203084
001451802 020__ $$z3031203089
001451802 0247_ $$a10.1007/978-3-031-20309-1$$2doi
001451802 035__ $$aSP(OCoLC)1353838344
001451802 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCQ$$dBRX$$dUKAHL
001451802 049__ $$aISEA
001451802 050_4 $$aTK5105.888
001451802 08204 $$a004.67/8$$223/eng/20230103
001451802 1112_ $$aInternational Conference on Web Information Systems and Applications$$n(19th :$$d2022 :$$cDalian, China).
001451802 24510 $$aWeb information systems and applications :$$b19th International Conference, WISA 2022, Dalian, China, September 16-18, 2022 : proceedings /$$cXiang Zhao, Shiyu Yang, Xin Wang, Jianxin Li (eds.).
001451802 24630 $$aWISA 2022
001451802 264_1 $$aCham :$$bSpringer,$$c[2022]
001451802 264_4 $$c©2022
001451802 300__ $$a1 online resource (xviii, 743 pages) :$$billustrations (chiefly color).
001451802 336__ $$atext$$btxt$$2rdacontent
001451802 337__ $$acomputer$$bc$$2rdamedia
001451802 338__ $$aonline resource$$bcr$$2rdacarrier
001451802 4901_ $$aLecture notes in computer science ;$$v13579
001451802 500__ $$aSelected conference papers.
001451802 500__ $$aIncludes author index.
001451802 5050_ $$aIntro -- Preface -- Organization -- Contents -- Knowledge Graph -- Temporal Knowledge Graph Embedding for Link Prediction -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Methodology -- 4.1 Structural Self-attention -- 4.2 Temporal Self-attention -- 4.3 Parameter Learning -- 4.4 Discussion -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Performance Comparison (RQ1) -- 5.3 Utility of Structural and Temporal Self-attention (RQ2) -- 5.4 Hyper-Parameter Studies (RQ3) -- 6 Conclusions -- References -- A Multi-modal Knowledge Graph Platform Based on Medical Data Lake
001451802 5058_ $$a1 Introduction -- 2 Related Work -- 3 Architecture of MMKGP -- 4 Translation-Based Model Enhanced by Prior Knowledge -- 4.1 TransE Model -- 4.2 Constraint for Relations -- 5 Knowledge Graph Completion with Multi-modal Data -- 5.1 Dataset -- 5.2 Evaluation Criterion -- 5.3 Model Training and Result -- 6 Knowledge Graph-Based Clinical Decision Support System -- 6.1 Link Prediction & Correction -- 6.2 Recommendation and Q&A System -- 7 Conclusion -- References -- Fusion of Natural Language and Knowledge Graph for Multi-hop Reasoning -- 1 Introduction -- 2 Related Works -- 3 Model -- 3.1 Description
001451802 5058_ $$a3.2 Framework -- 3.3 Subgraph Retrieval -- 3.4 Structural Fusion -- 3.5 Relation Reasoning -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Model Comparison -- 5 Conclusion -- References -- Commonsense Knowledge Construction with Concept and Pretrained Model -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Framework of CG&BF -- 3.2 Concept-Based Generator -- 3.3 BERT-Based Filter -- 4 Experiments -- 4.1 Experiment Setup -- 4.2 Model Comparison -- 5 Conclusion -- References -- Simplifying Knowledge-Aware Aggregation for Knowledge Graph Collaborative Filtering -- 1 Introduction
001451802 5058_ $$a2 Related Work -- 3 Task Formulation -- 4 Methodology -- 4.1 Personalized Knowledge Aggregation -- 4.2 User Aggregation -- 4.3 Prediction Layer -- 5 Experiments -- 5.1 Datasets -- 5.2 Baselines -- 5.3 Experimental Settings -- 5.4 Performance Comparison (RQ1) -- 5.5 Ablation Studies (RQ2) -- 6 Conclusion -- References -- Bi-Directional Neighborhood-Aware Network for Entity Alignment in Knowledge Graphs -- 1 Introduction -- 2 Related Work -- 2.1 Embedding-Based Methods -- 2.2 Phenomenon of Long-Tail -- 3 Problem Formalization -- 4 Methodology -- 4.1 Neighborhood Embedding
001451802 5058_ $$a4.2 Entity Name Embedding -- 4.3 Feature Fusion with Bi-attention -- 4.4 Alignment and Training -- 5 Experiments -- 5.1 Experiment Setting -- 5.2 Main Result -- 5.3 Ablation Study -- 5.4 Evaluation by Degrees Interval -- 5.5 Robustness on Datasets -- 6 Conclusion -- References -- SAREM: Semi-supervised Active Heterogeneous Entity Matching Framework -- 1 Introduction -- 2 Related Work -- 2.1 Entity Matching -- 2.2 EM Based on Active Learning -- 3 Problem Statement and Definition -- 4 The Framework: Sarem -- 4.1 Data Augmentation -- 4.2 Feature Extraction -- 4.3 Example Selection
001451802 506__ $$aAccess limited to authorized users.
001451802 520__ $$aThis book constitutes the proceedings of the 19th International Conference on Web Information Systems and Applications, WISA 2022, held in Dalian, China, in September 2022. The 45 full papers and 19 short papers presented were carefully reviewed and selected from 212 submissions. The papers are grouped in topical sections on knowledge graph, natural language processing, world wide web, machine learning, query processing and algorithm, recommendation, data privacy and security, and blockchain.
001451802 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 3, 2023).
001451802 650_0 $$aWorld Wide Web$$vCongresses.
001451802 650_0 $$aArtificial intelligence$$vCongresses.
001451802 655_0 $$aElectronic books.
001451802 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001451802 655_7 $$aConference papers and proceedings.$$2lcgft
001451802 7001_ $$aZhao, Xiang,$$eeditor.
001451802 7001_ $$aYang, Shiyu,$$eeditor.
001451802 7001_ $$aWang, Xin,$$eeditor.
001451802 7001_ $$aLi, Jianxin$$c(Senior lecturer),$$eeditor.
001451802 77608 $$iPrint version: $$z3031203089$$z9783031203084$$w(OCoLC)1346531656
001451802 830_0 $$aLecture notes in computer science ;$$v13579.
001451802 852__ $$bebk
001451802 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-20309-1$$zOnline Access$$91397441.1
001451802 909CO $$ooai:library.usi.edu:1451802$$pGLOBAL_SET
001451802 980__ $$aBIB
001451802 980__ $$aEBOOK
001451802 982__ $$aEbook
001451802 983__ $$aOnline
001451802 994__ $$a92$$bISE