000845509 000__ 04811cam\a2200541Ii\4500 000845509 001__ 845509 000845509 005__ 20230306144853.0 000845509 006__ m\\\\\o\\d\\\\\\\\ 000845509 007__ cr\cn\nnnunnun 000845509 008__ 180808s2018\\\\si\a\\\\ob\\\\000\0\eng\d 000845509 019__ $$a1049609153 000845509 020__ $$a9789811315169$$q(electronic book) 000845509 020__ $$a9811315167$$q(electronic book) 000845509 020__ $$z9789811315152 000845509 020__ $$z9811315159 000845509 0247_ $$a10.1007/978-981-13-1516-9$$2doi 000845509 035__ $$aSP(OCoLC)on1048004030 000845509 035__ $$aSP(OCoLC)1048004030$$z(OCoLC)1049609153 000845509 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dN$T$$dEBLCP$$dYDX$$dOCLCF$$dUAB 000845509 049__ $$aISEA 000845509 050_4 $$aQA76.9.N38 000845509 08204 $$a006.3/5$$223 000845509 1001_ $$aMishra, Abhijit,$$eauthor. 000845509 24510 $$aCognitively inspired natural language processing :$$ban investigation based on eye-tracking /$$cAbhijit Mishra, Pushpak Bhattacharyya. 000845509 264_1 $$aSingapore :$$bSpringer,$$c2018. 000845509 300__ $$a1 online resource (xvii, 174 pages) :$$billustrations. 000845509 336__ $$atext$$btxt$$2rdacontent 000845509 337__ $$acomputer$$bc$$2rdamedia 000845509 338__ $$aonline resource$$bcr$$2rdacarrier 000845509 4901_ $$aCognitive intelligence and robotics,$$x2520-1956 000845509 504__ $$aIncludes bibliographical references. 000845509 5050_ $$aIntro; Preface; Acknowledgements; Contents; About the Authors; 1 Introduction; 1.1 Cognitive Data: A Valuable By-product of Annotation; 1.2 Human Eye-Movement and Eye-Tracking Technology; 1.2.1 The Visual System: How Do We See?; 1.2.2 Eye-Tracking Technology; 1.2.3 History of Development of Eye-Trackers; 1.2.4 Eye-Tracking Systems: Invasive and Non-invasive; 1.2.5 Tools for Gaze Data Recording and Analysis; 1.2.6 Eye Movement in Reading and Language Processing; 1.3 Theme of the Monograph; 1.3.1 Research Objective 1: Assessing Cognitive Effort in Text Annotation 000845509 5058_ $$a1.3.2 Research Objective 2: Extracting Cognitive Features for Text Classification1.4 Roadmap of the Book; References; 2 Applications of Eye Tracking in Language Processing and Other Areas; 2.1 Eye Movement and Reading: A Psycholinguistic Perspective; 2.1.1 The Eye-Mind Hypothesis: Just and Carpenters' Theory of Reading; 2.1.2 Basic Characteristics of Eye Movement in Reading; 2.1.3 Effects of Lexical and Syntactic Complexities on Eye Movement; 2.1.4 Models for Eye-Movement Control During Reading; 2.1.5 Comparing Eye-Movement Patterns: Measures for Scanpath Similarity 000845509 5058_ $$a2.2 Eye-Movement Behavior and Text Annotation2.2.1 Study of Text Translation Annotation; 2.2.2 Study of Word Sense Annotation; 2.2.3 Study of Sentiment Annotation; 2.2.4 Cognitive Cost Model for Annotation-A Case Study of Named Entity Marking; 2.3 Eye-Movement Data for Development and Evaluation of NLP Systems; 2.3.1 Part-of-Speech Tagging; 2.3.2 Sentence Compression; 2.3.3 Machine Translation Evaluation; 2.4 Eye Tracking: Application Areas Other than Reading and Language Processing; 2.4.1 Neuroscience; 2.4.2 Industrial Engineering and Human Factors 000845509 5058_ $$a2.4.3 Human-Computer Interaction and User Experience2.4.4 Marketing/Advertisement; References; Part I Assessing Cognitive Effort in Annotation; 3 Estimating Annotation Complexities of Text Using Gaze and Textual Information; 3.1 Estimating Text Translation Complexity; 3.1.1 Translation Complexity Index-Motivation, Utility, and Background; 3.1.2 Prediction Framework for Translation Complexity; 3.1.3 Using Eye Tracking for TCI Annotation; 3.1.4 Computing TCI Using Eye-Tracking Database; 3.1.5 Relating TCI to Linguistic Features; 3.1.6 Lexical Features; 3.1.7 Syntactic Features 000845509 5058_ $$a3.1.8 Semantic Features3.1.9 Translation Feature; 3.1.10 Experiment and Results; 3.1.11 Discussion: Correlation Between Translation Complexity and Machine Translation Accuracy; 3.2 Measuring Sentiment Annotation Complexity; 3.2.1 Sentiment Annotation Complexity: Motivation, Utility and Background; 3.2.2 Understanding Sentiment Annotation Complexity; 3.2.3 Creation of Dataset Annotated with SAC; 3.2.4 Eye-Tracking Experimental Setup; 3.2.5 Calculating SAC from Eye-Movement Data; 3.2.6 Linguistic Features for Predicting Sentiment Annotation Complexity; 3.2.7 Predictive Framework for SAC 000845509 506__ $$aAccess limited to authorized users. 000845509 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 8, 2018). 000845509 650_0 $$aNatural language processing (Computer science) 000845509 650_0 $$aMachine learning. 000845509 650_0 $$aEye tracking. 000845509 7001_ $$aBhattacharyya, Pushpak,$$eauthor. 000845509 77608 $$iPrint version: $$z9811315159$$z9789811315152$$w(OCoLC)1039604813 000845509 830_0 $$aCognitive intelligence and robotics. 000845509 852__ $$bebk 000845509 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-13-1516-9$$zOnline Access$$91397441.1 000845509 909CO $$ooai:library.usi.edu:845509$$pGLOBAL_SET 000845509 980__ $$aEBOOK 000845509 980__ $$aBIB 000845509 982__ $$aEbook 000845509 983__ $$aOnline 000845509 994__ $$a92$$bISE