LEADER 02873nam 2200613Ia 450 001 9910451543303321 005 20200520144314.0 010 $a1-281-12970-4 010 $a9786611129705 010 $a0-335-23020-2 035 $a(CKB)1000000000410111 035 $a(EBL)316320 035 $a(OCoLC)614472014 035 $a(SSID)ssj0000121193 035 $a(PQKBManifestationID)11910123 035 $a(PQKBTitleCode)TC0000121193 035 $a(PQKBWorkID)10092958 035 $a(PQKB)10701428 035 $a(MiAaPQ)EBC316320 035 $a(Au-PeEL)EBL316320 035 $a(CaPaEBR)ebr10197012 035 $a(CaONFJC)MIL112970 035 $a(OCoLC)781321007 035 $a(EXLCZ)991000000000410111 100 $a20070202d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aChildren's mathematics 4-15$b[electronic resource] $elearning from errors and misconceptions /$fJulie Ryan, Julian Williams 210 $aMaidenhead $cMcGraw-Hill/Open University Press$d2007 215 $a1 online resource (262 p.) 300 $aDescription based upon print version of record. 311 $a0-335-22042-8 320 $aIncludes bibliographical references and index. 327 $aFront cover; Half title; Title; Copyright; Contents; Acknowledgements; Chapter 1 Introduction; Chapter 2 Learning from errors and misconceptions; Chapter 3 Children's mathematical discussions; Chapter 4 Developing number; Chapter 5 Shape, space and measurement; Chapter 6 From number to algebra; Chapter 7 Data-handling, graphicacy, probability and statistics; Chapter 8 Pre-service teachers' mathematics subject matter knowledge; Chapter 9 Learning and teaching mathematics: towards a theory of pedagogy; Appendix 1: Common errors and misconceptions; Appendix 2: Discussion prompt sheets; Glossary 327 $aReferencesIndex; Back cover 330 $aDevelops concepts for teachers to use in organizing their understanding and knowledge of children's mathematics. This book offers guidance for classroom teaching and concludes with theoretical accounts of learning and teaching. It transforms research on diagnostic errors into knowledge for teaching, teacher education and research on teaching. 606 $aMathematics$xStudy and teaching (Elementary) 606 $aMathematics$xStudy and teaching (Secondary) 608 $aElectronic books. 615 0$aMathematics$xStudy and teaching (Elementary) 615 0$aMathematics$xStudy and teaching (Secondary) 676 $a510.71 700 $aRyan$b Julie$g(Julie T.)$0936815 701 $aWilliams$b Julian$g(Julian S.)$0936816 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910451543303321 996 $aChildren's mathematics 4-15$92110040 997 $aUNINA LEADER 03780nam 2200829Ia 450 001 9910970830403321 005 20251117115106.0 010 $a1-134-85522-2 010 $a1-134-85523-0 010 $a1-280-10553-4 010 $a0-203-20140-X 024 7 $a10.4324/9780203201404 035 $a(CKB)111087027071778 035 $a(EBL)168886 035 $a(OCoLC)475876019 035 $a(SSID)ssj0000112954 035 $a(PQKBManifestationID)11129833 035 $a(PQKBTitleCode)TC0000112954 035 $a(PQKBWorkID)10098852 035 $a(PQKB)11693963 035 $a(MiAaPQ)EBC168886 035 $a(Au-PeEL)EBL168886 035 $a(CaPaEBR)ebr10166581 035 $a(CaONFJC)MIL10553 035 $a(OCoLC)936888245 035 $a(OCoLC)625027022 035 $a(EXLCZ)99111087027071778 100 $a19931108d1994 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBlack women, writing, and identity $emigrations of the subject /$fCarole Boyce Davies 205 $a1st ed. 210 $aLondon ;$aNew York $cRoutledge$d1994 215 $a1 online resource (193 p.) 300 $aDescription based upon print version of record. 311 08$a0-415-10087-9 311 08$a0-415-10086-0 320 $aIncludes bibliographical references and index. 327 $aBOOKCOVER; CONTENTS; ACKNOWLEDGMENTS; 1 INTRODUCTION: MIGRATORY SUBJECTIVITIES; 2 NEGOTIATING THEORIES OR "GOING A PIECE OF THE WAY WITH THEM"; 3 DECONSTRUCTING AFRICAN FEMALE SUBJECTIVITIES; 4 FROM "POST-COLONIALITY" TO UPRISING TEXTUALITIES; 5 WRITING HOME; 6 MOBILITY, EMBODIMENT AND RESISTANCE; 7 OTHER TONGUES; NOTES; BIBLIOGRAPHY; INDEX 330 $aBlack Women Writing and Identity is an exciting work by one of the most imaginative and acute writers around. The book explores a complex and fascinating set of interrelated issues, establishing the significance of such wide-ranging subjects as: * re-mapping, re-naming and cultural crossings * tourist ideologies and playful world travelling * gender, heritage and identity * African women's writing and resistance to domination * marginality, effacement and decentering * gender, language and the politics of location Carole Boyce-Davies is at the forefront of 606 $aAmerican literature$xAfrican American authors$xHistory and criticism 606 $aEnglish literature$zForeign countries$xHistory and criticism 606 $aAmerican literature$xWomen authors$xHistory and criticism 606 $aEnglish literature$xBlack authors$xHistory and criticism 606 $aEnglish literature$xWomen authors$xHistory and criticism 606 $aIdentity (Psychology) in literature 606 $aAfrican Americans in literature 606 $aAuthorship$xSex differences 606 $aBlack people in literature 606 $aWomen and literature 615 0$aAmerican literature$xAfrican 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$a(EXLCZ)995840000000091732 100 $a20220924d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNatural Language Processing and Chinese Computing $e11th CCF International Conference, NLPCC 2022, Guilin, China, September 24?25, 2022, Proceedings, Part II /$fedited by Wei Lu, Shujian Huang, Yu Hong, Xiabing Zhou 205 $a1st ed. 2022. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2022. 215 $a1 online resource (385 pages) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v13552 311 08$a9783031171888 311 08$a3031171888 327 $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 -- 2 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 -- 5 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 -- 6 Future Work -- References -- NLP Applications and Text Mining (Poster). 327 $aContinuous 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 -- Bidirectional 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 -- 4.3 Evaluation Metrics -- 4.4 Ablation Study -- 4.5 Performance on Tail Labels -- 5 Conclusions -- References -- MGEDR: A Molecular Graph Encoder for Drug Recommendation -- 1 Introduction -- 2 Related Works -- 2.1 Drug Recommendation -- 2.2 Molecular Graph Representation -- 3 Problem Formulation -- 4 The MGEDR Model -- 4.1 Patient Encoder -- 4.2 Medicine Encoder -- 4.3 Functional Groups Encoder -- 4.4 Medicine Representation -- 4.5 Optimization -- 5 Experiments -- 5.1 Dataset and Metrics -- 5.2 Results -- 5.3 Ablations -- 6 Conclusion -- References -- Student Workshop (Poster) -- Semi-supervised Protein-Protein Interactions Extraction Method Based on Label Propagation and Sentence Embedding -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Problem Formulation -- 3.2 Overall Workflow. 327 $a3.3 Label Propagation -- 3.4 Sentence Embedding -- 3.5 CNN Classifier -- 4 Results -- 4.1 Datasets and Preprocessing -- 4.2 Experimental Results -- 4.3 Hyperparameter Analysis -- 5 Conclusion -- References -- Construction and Application of a Large-Scale Chinese Abstractness Lexicon Based on Word Similarity -- 1 Introduction -- 2 Data and Method -- 2.1 Data -- 2.2 Method -- 3 Experiment -- 4 Construction and Evaluation -- 5 Application -- 5.1 Cross-Language Comparison -- 5.2 Chinese Text Readability Auto-evaluation -- 6 Conclusion -- References -- Stepwise Masking: A Masking Strategy Based on Stepwise Regression for Pre-training -- 1 Introduction -- 2 Methodology -- 2.1 Three-Stage Framework -- 2.2 Stepwise Masking -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Main Results -- 3.4 Effectiveness of Stepwise Masking -- 3.5 Effect of Dynamic in Stepwise Masking -- 3.6 Case Study -- 4 Conclusion and Future Work -- References -- Evaluation Workshop (Poster) -- Context Enhanced and Data Augmented W2NER System for Named Entity Recognition -- 1 Introduction -- 2 Related Work -- 3 The Proposed Approach -- 3.1 Task Definition -- 3.2 Model Structure -- 3.3 Data Augmentation -- 3.4 Result Ensemble -- 4 Experiments -- 4.1 Dataset and Metric -- 4.2 Experiment Settings -- 4.3 Baselines -- 4.4 Results and Analysis -- 5 Conclusion -- References -- Multi-task Hierarchical Cross-Attention Network for Multi-label Text Classification -- 1 Introduction -- 2 Related Work -- 2.1 Hierarchical Multi-label Text Classification -- 2.2 Representation of Scientific Literature -- 3 Methodology -- 3.1 Representation Layer -- 3.2 Hierarchical Cross-Attention Recursive Layer -- 3.3 Hierarchical Prediction Layer -- 3.4 Rebalanced Loss Function -- 4 Experiment -- 4.1 Dataset and Evaluation -- 4.2 Experimental Settings -- 4.3 Results and Discussions. 327 $a4.4 Module Analysis -- 5 Conclusion -- References -- An Interactive Fusion Model for Hierarchical Multi-label Text Classification -- 1 Introduction -- 2 Related Work -- 3 Task Definition -- 4 Method -- 4.1 Shared Encoder Module -- 4.2 Task-Specific Module -- 4.3 Training and Inference -- 5 Experiment -- 6 Conclusion -- References -- Scene-Aware Prompt for Multi-modal Dialogue Understanding and Generation -- 1 Introduction -- 2 Task Introduction -- 2.1 Problem Definition -- 2.2 Evaluation Metric -- 2.3 Dateset -- 3 Main Methods -- 3.1 Multi-tasking Multi-modal Dialogue Understanding -- 3.2 Scene-Aware Prompt Multi-modal Dialogue Generation -- 3.3 Training and Inference -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Main Results -- 4.3 Ablation Study -- 4.4 Online Results -- 5 Conclusion -- References -- BIT-WOW at NLPCC-2022 Task5 Track1: Hierarchical Multi-label Classification via Label-Aware Graph Convolutional Network -- 1 Introduction -- 2 Approach -- 2.1 Context-Aware Label Embedding -- 2.2 Graph-Based Hierarchical Label Modeling -- 2.3 Curriculum Learning Strategy -- 2.4 Ensemble Learning and Post Editing -- 3 Experiments -- 3.1 Dataset and Experiment Settings -- 3.2 Main Results -- 3.3 Analysis -- 4 Related Work -- 5 Conclusion -- References -- CDAIL-BIAS MEASURER: A Model Ensemble Approach for Dialogue Social Bias Measurement -- 1 Introduction -- 2 Related Work -- 2.1 Shared Tasks -- 2.2 Solution Models -- 3 Dataset -- 4 Method -- 4.1 Models Selection -- 4.2 Fine-Tuning Strategies -- 4.3 Ensembling Strategy -- 5 Result -- 5.1 Preliminary Screening -- 5.2 Model Ensemble -- 5.3 Ensemble Size Effect -- 5.4 Discussion -- 6 Conclusion -- References -- A Pre-trained Language Model for Medical Question Answering Based on Domain Adaption -- 1 Introduction -- 2 Related Work -- 2.1 Encoder-Based -- 2.2 Decoder-Based -- 2.3 Encoder-Decoder-Based. 327 $a3 Description of the Competition -- 3.1 Evaluation Metrics -- 3.2 Datasets -- 4 Solution -- 4.1 Model Introduction -- 4.2 Strategy -- 4.3 Model Optimization -- 4.4 Model Evaluation -- 5 Conclusion -- References -- Enhancing Entity Linking with Contextualized Entity Embeddings -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dual Encoder -- 3.2 LUKE-Based Cross-Encoder -- 4 Experiments -- 4.1 Data -- 4.2 Candidate Retrieval -- 4.3 Candidate Reranking -- 5 Conclusion -- References -- A Fine-Grained Social Bias Measurement Framework for Open-Domain Dialogue Systems -- 1 Introduction -- 2 Related Work -- 2.1 Fine Grained Dialogue Social Bias Measurement -- 2.2 Application of Contrastive Learning in NLP Tasks -- 2.3 Application of Prompt Learning in NLP Tasks -- 3 Fine-Grain Dialogue Social Bias Measurement Framework -- 3.1 General Representation Module -- 3.2 Two-Stage Prompt Learning Module -- 3.3 Contrastive Learning Module -- 4 Experiment -- 4.1 Dataset -- 4.2 Experimental Setup -- 4.3 Results and Analysis -- 5 Conclusion -- References -- Dialogue Topic Extraction as Sentence Sequence Labeling -- 1 Introduction -- 2 Related Work -- 2.1 Dialogue Topic Information -- 2.2 Sequence Labeling -- 3 Methodology -- 3.1 Task Definition -- 3.2 Topic Extraction Model -- 3.3 Ensemble Model -- 4 Experiments -- 4.1 Dataset -- 4.2 Results and Analysis -- 5 Conclusion -- References -- Knowledge Enhanced Pre-trained Language Model for Product Summarization -- 1 Introduction -- 2 Related Work -- 2.1 Encoder-Decoder Transformer -- 2.2 Decoder-Only Transformer -- 3 Description of the Competition -- 4 Dataset Introduction -- 4.1 Textual Data -- 4.2 Image Data -- 5 Model Solution -- 5.1 Model Introduction -- 5.2 Model Training -- 6 Model Evaluation -- 7 Conclusion -- References -- Augmented Topic-Specific Summarization for Domain Dialogue Text -- 1 Introduction. 327 $a2 Related Work. 330 $aThis two-volume set of LNAI 13551 and 13552 constitutes the refereed proceedings of the 11th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2022, held in Guilin, China, in September 2022. The 62 full papers, 21 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 327 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v13552 606 $aArtificial intelligence 606 $aArtificial Intelligence 615 0$aArtificial intelligence. 615 14$aArtificial Intelligence. 676 $a495.10285 676 $a006.35 702 $aLu$b Wei 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910595031503321 996 $aNatural Language Processing and Chinese Computing$91912515 997 $aUNINA