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001449877 001__ 1449877
001449877 003__ OCoLC
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001449877 020__ $$a9783031171895$$q(electronic bk.)
001449877 020__ $$a3031171896$$q(electronic bk.)
001449877 020__ $$z9783031171888
001449877 0247_ $$a10.1007/978-3-031-17189-5$$2doi
001449877 035__ $$aSP(OCoLC)1346150881
001449877 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCF$$dOCLCQ$$dUKAHL
001449877 049__ $$aISEA
001449877 050_4 $$aQA76.9.N38
001449877 08204 $$a006.3/5$$223/eng/20220928
001449877 1112_ $$aNLPCC (Conference)$$n(11th :$$d2022 :$$cGuilin, China)
001449877 24510 $$aNatural language processing and Chinese computing :$$b11th CCF International Conference, NLPCC 2022, Guilin, China, September 24-25, 2022, proceedings.$$nPart II /$$cWei Lu, Shujian Huang, Yu Hong, Xiabing Zhou (eds.).
001449877 24630 $$aNLPCC 2022
001449877 264_1 $$aCham :$$bSpringer,$$c[2022]
001449877 264_4 $$c©2022
001449877 300__ $$a1 online resource (xxxi, 363 pages) :$$billustrations (chiefly color).
001449877 336__ $$atext$$btxt$$2rdacontent
001449877 337__ $$acomputer$$bc$$2rdamedia
001449877 338__ $$aonline resource$$bcr$$2rdacarrier
001449877 4901_ $$aLecture notes in computer science. Lecture notes in artificial intelligence ;$$v13552
001449877 4901_ $$aLNCS sublibrary: SL7 - Artificial intelligence
001449877 500__ $$aInternational conference proceedings.
001449877 500__ $$aIncludes author index.
001449877 5050_ $$aIntro -- Preface -- Organization -- Contents -- Part II -- Contents -- Part I -- Question Answering (Poster) -- Faster and Better Grammar-Based Text-to-SQL Parsing via Clause-Level Parallel Decoding and Alignment Loss -- 1 Introduction -- 2 Related Works -- 3 Our Proposed Model -- 3.1 Grammar-Based Text-to-SQL Parsing -- 3.2 Clause-Level Parallel Decoding -- 3.3 Clause-Level Alignment Loss -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 4.3 Analysis -- 5 Conclusions -- References -- Two-Stage Query Graph Selection for Knowledge Base Question Answering -- 1 Introduction
001449877 5058_ $$a2 Our Approach -- 2.1 Query Graph Generation -- 2.2 Two-Stage Query Graph Selection -- 3 Experiments -- 3.1 Experimental Setup -- 3.2 Main Results -- 3.3 Discussion and Analysis -- 4 Related Work -- 5 Conclusions -- References -- Plug-and-Play Module for Commonsense Reasoning in Machine Reading Comprehension -- 1 Introduction -- 2 Methodology -- 2.1 Task Formulation -- 2.2 Proposed Module: PIECER -- 2.3 Plugging PIECER into MRC Models -- 3 Experiments -- 3.1 Datasets -- 3.2 Base Models -- 3.3 Experimental Settings -- 3.4 Main Results -- 3.5 Analysis and Discussions -- 4 Related Work
001449877 5058_ $$a5 Conclusion -- References -- Social Media and Sentiment Analysis (Poster) -- FuDFEND: Fuzzy-Domain for Multi-domain Fake News Detection -- 1 Introduction -- 2 Related Work -- 2.1 Fake News Detection Methods -- 2.2 Multi-domain Rumor Task -- 3 FuDFEND: Fuzzy-Domain Fake News Detection Model -- 3.1 Membership Function -- 3.2 Feature Extraction -- 3.3 Domain Gate -- 3.4 Fake News Prediction and Loss Function -- 4 Experiment -- 4.1 Dataset -- 4.2 Experiment Setting -- 4.3 Train Membership Function and FuDFEND -- 4.4 Experiment on Weibo21 -- 4.5 Experiment on Thu Dataset -- 5 Conclusion
001449877 5058_ $$a6 Future Work -- References -- NLP Applications and Text Mining (Poster) -- Continuous Prompt Enhanced Biomedical Entity Normalization -- 1 Introduction -- 2 Related Work -- 2.1 Biomedical Entity Normalization -- 2.2 Prompt Learning and Contrastive Loss -- 3 Our Method -- 3.1 Prompt Enhanced Scoring Mechanism -- 3.2 Contrastive Loss Enhanced Training Mechanism -- 4 Experiments and Analysis -- 4.1 Dataset and Evaluation -- 4.2 Data Preprocessing -- 4.3 Experiment Setting -- 4.4 Overall Performance -- 4.5 Ablation Study -- 5 Conclusion -- References
001449877 5058_ $$aBidirectional Multi-channel Semantic Interaction Model of Labels and Texts for Text Classification -- 1 Introduction -- 2 Model -- 2.1 Preliminaries -- 2.2 Bidirectional Multi-channel Semantic Interaction Model -- 3 Experiments -- 3.1 Experimental Settings -- 3.2 Results and Analysis -- 3.3 Ablation Test -- 4 Conclusions -- References -- Exploiting Dynamic and Fine-grained Semantic Scope for Extreme Multi-label Text Classification -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Notation -- 3.2 TReaderXML -- 4 Experiments -- 4.1 Datasets and Preprocessing -- 4.2 Baselines
001449877 506__ $$aAccess limited to authorized users.
001449877 520__ $$aThis two-volume set of LNAI 13551 and 13552 constitutes the refereed proceedings of the 11th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2022, held in Guilin, China, in September 2022. The 62 full papers, 21 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 327 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability.
001449877 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 28, 2022).
001449877 650_0 $$aNatural language processing (Computer science)$$vCongresses.
001449877 650_0 $$aChinese language$$xData processing$$vCongresses.
001449877 655_0 $$aElectronic books.
001449877 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001449877 655_7 $$aConference papers and proceedings.$$2lcgft
001449877 7001_ $$aLu, Wei,$$eeditor.
001449877 7001_ $$aHuang, Shujian,$$eeditor.
001449877 7001_ $$aHong, Yu,$$eeditor.
001449877 7001_ $$aZhou, Xiabing,$$eeditor.
001449877 830_0 $$aLecture notes in computer science ;$$v13552.
001449877 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001449877 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001449877 852__ $$bebk
001449877 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-17189-5$$zOnline Access$$91397441.1
001449877 909CO $$ooai:library.usi.edu:1449877$$pGLOBAL_SET
001449877 980__ $$aBIB
001449877 980__ $$aEBOOK
001449877 982__ $$aEbook
001449877 983__ $$aOnline
001449877 994__ $$a92$$bISE