LEADER 13827nam 22008895 450 001 996466233703316 005 20200901132908.0 010 $a3-319-27101-6 024 7 $a10.1007/978-3-319-27101-9 035 $a(CKB)4340000000001233 035 $a(SSID)ssj0001584802 035 $a(PQKBManifestationID)16265240 035 $a(PQKBTitleCode)TC0001584802 035 $a(PQKBWorkID)14865081 035 $a(PQKB)10497444 035 $a(DE-He213)978-3-319-27101-9 035 $a(MiAaPQ)EBC5587997 035 $a(Au-PeEL)EBL5587997 035 $a(OCoLC)932170412 035 $a(PPN)190529725 035 $a(EXLCZ)994340000000001233 100 $a20151119d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in Artificial Intelligence and Its Applications$b[electronic resource] $e14th Mexican International Conference on Artificial Intelligence, MICAI 2015, Cuernavaca, Morelos, Mexico, October 25-31, 2015, Proceedings, Part II /$fedited by Obdulia Pichardo Lagunas, Oscar Herrera Alcántara, Gustavo Arroyo Figueroa 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (XXIX, 619 p. 197 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence ;$v9414 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-319-27100-8 327 $aIntro -- Preface -- Conference Organization -- Contents - Part II -- Contents - Part I -- Invited Papers -- Measuring Non-compositionality of Verb-Noun Collocations Using Lexical Functions and WordNet Hypernyms -- Abstract -- 1 Introduction -- 2 Related Work on Non-compositionality of Collocations -- 3 Lexical Functions as a Concept of the Meaning-Text Theory -- 3.1 Meaning-Text Theory (MTT) -- 3.2 Lexical Function -- 3.3 Lexical Functions in Verb-Noun Collocations -- 4 Non-compositionality in Terms of Lexical Function Detection Using WordNet Hypernyms -- 5 Experiments -- 6 Results and Discussion -- 7 Conclusions and Future Work -- Acknowledgements -- References -- Fuzzy-Probabilistic Estimation of the Electric Vehicles Energy Consumption -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 Framework -- 2.2 Fuzzy-Probabilistic Methodology -- 3 Numerical Example -- 4 Conclusions -- References -- Natural Language Processing Applications -- Data-Driven Unsupervised Evaluation of Automatic Text Summarization Systems -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Our Approach -- 4 Data -- 5 Experiments. Results. Discussion -- 5.1 Experiment with Informants -- 5.2 Preliminary Evaluation of the Summaries -- 5.3 Automatic Keywords Extraction -- 5.4 Comparison of Keywords Given by Different Groups of Informants -- 6 Conclusion and Future Work -- Acknowledgements -- References -- Extractive Single-Document Summarization Based on Global-Best Harmony Search and a Greedy Local Optimizer -- Abstract -- 1 Introduction -- 2 Problem Statement and Its Mathematical Formulation -- 3 The Proposed Memetic Algorithm -- 3.1 Greedy Local Optimizer -- 4 Experiment and Evaluation -- 4.1 Parameter Tuning -- 4.2 Results -- 5 Conclusions and Future Work -- Acknowledgments -- References -- SVD-LDA: Topic Modeling for Full-Text Recommender Systems -- 1 Introduction. 327 $a2 LDA and sLDA -- 2.1 Latent Dirichlet Allocation -- 2.2 Supervised LDA -- 3 SVD in Recommender Systems -- 3.1 Basic SVD Model in Collaborative Filtering -- 3.2 Cold Start, Additional Information, and Content -- 4 SVD-LDA -- 4.1 SVD-LDA: Exact Sampling -- 4.2 SVD-LDA: First Order Approximation -- 4.3 Variations of SVD-LDA -- 5 Evaluation -- 5.1 Dataset -- 5.2 RMSE Improves with LDA Training -- 5.3 SVD-LDA Recommends Better Than SVD -- 5.4 Predictors for Demographic Clusters -- 6 Conclusion -- References -- Movies Recommendation Based on Opinion Mining in Twitter -- 1 Introduction -- 2 Classification Models for Opinion Mining -- 2.1 Tokenization -- 2.2 Pre-processing -- 2.3 Classification Models -- 3 Experimental Results -- 3.1 Data Collection -- 3.2 Tokenization Strategies -- 3.3 Pre-processing Strategies -- 3.4 Movies Recommendation -- 4 Related Work -- 5 Conclusions and Future Work -- References -- Inferring Sentiment-Based Priors in Topic Models -- 1 Introduction -- 2 Latent Dirichlet Allocation -- 2.1 Notation and the Basic LDA Model -- 2.2 LDA Extensions -- 2.3 Topic Models for Sentiment Analysis -- 3 Learning Sentiment Priors with the EM Algorithm -- 4 Experimental Results -- 5 Conclusion -- References -- Analysis of Negation Cues for Semantic Orientation Classification of Reviews in Spanish -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Corpus and Linguistic Knowledge -- 3.1 Review Texts Corpus -- 3.2 Linguistic Knowledge -- 3.3 Negation -- 4 Methods for Semantic Orientation Classification -- 4.1 Unsupervised Method -- 4.2 Supervised Method -- 5 Results and Discussion -- 5.1 Unsupervised Method -- 5.2 Supervised Method -- 5.3 Discussion -- 6 Conclusions -- Acknowledgments -- References -- Detecting Social Spammers in Colombia 2014 Presidential Election -- 1 Introduction -- 2 Related Work -- 3 Background on the Colombian Election. 327 $a4 Data Collection and Ground Truth Creation -- 4.1 Dataset -- 4.2 Ground Truth -- 5 Detecting Social Spammers -- 5.1 Features -- 5.2 Semi-Supervised Detection -- 5.3 Supervised Detection -- 6 Discussion -- 7 Conclusions and Future Work -- References -- NLP Methodology as Guidance and Verification of the Data Mining of Survey ENSANUT 2012 -- Abstract -- 1 Introduction -- 2 Data -- 3 NLP Pipeline -- 3.1 Text Annotation -- 3.2 Lemma Classification by Collocation -- 3.3 Merging Lists of Lemmas and Adding Intentionality -- 3.4 Corpus Division for Focused Queries -- 3.5 Feature Extraction -- 4 Model and Results -- 4.1 Pre-processing Data Using the Selected Features -- 4.2 Frequency Histograms -- 4.3 Epsilon and Scores -- 4.4 Testing the Classifier -- 4.5 Confusion Matrix of the Test Set -- 5 Conclusion -- Acknowledgments -- References -- Educational Applications -- A Comparative Framework to Evaluate Recommender Systems in Technology Enhanced Learning: a Case Study -- 1 Introduction -- 2 Background -- 3 The Proposed Comparative Framework -- 4 The Framework in Action: A Case Study -- 4.1 Brief Overview of Subject Systems -- 5 Performance Analysis -- 5.1 Google -- 5.2 Slideshare -- 5.3 Youtube -- 5.4 Connexions -- 5.5 MERLOT and ARIADNE -- 6 Summarising the Results: Comparative Analysis -- 6.1 Limitations of the Experiment -- 7 Conclusions and Future Work -- References -- An Affective and Cognitive Tutoring System for Learning Programming -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Java Sensei Architecture -- 4 Affective Recognition and Feedback -- 5 Experiments and Results -- 6 Conclusions and Future Work -- Funding -- References -- Strategic Learning Meta-Model (SLM): Architecture of the Personalized Virtual Learning Environment (PVLE) Based on the Cloud Computing -- Abstract -- 1 Introduction -- 1.1 Conceptual Framework. 327 $a1.2 Learning Evaluation and Learning Styles -- 1.3 Personalization of Learning Assessment -- 1.4 Research Focused in Evaluation of E-Learning -- 1.5 Research Based on the Design and Application of Ontologies -- 1.6 Researches Focused on Learning Personalization and Teaching -- 1.7 Ontology for Personalized Learning Activities Based on a Cognitive Theory -- 2 Methodology -- 3 Personalized Virtual Learning Environment (PVLE) with a Ontological Model (OM) -- 3.1 LMS Architecture -- 3.2 VLE Architecture -- 3.3 Ontological Model (OM) Architecture -- 4 Study Case -- 4.1 Design of the Ontology Using the Methodology GODeM and OntoDesign Graphics Notation -- 4.2 Implementation of the Ontology Prot00E9g00E9 -- 4.3 Results -- 5 Conclusions -- References -- Open Student Model for Blended Training in the Electrical Tests Domain -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Blended Training Model -- 3.1 VRS for Electrical Test Training -- 4 Trainee Model -- 5 Conclusions and Future Work -- References -- Applying Data Mining Techniques to Identify Success Factors in Students Enrolled in Distance Learning: A Case Study -- Abstract -- 1 Introduction -- 2 Methodology -- 3 Data Collection -- 4 Results and Interpretation -- 5 Conclusions -- References -- Automatic Evaluation of Music Students -- 1 Introduction -- 2 Feature Extraction -- 2.1 The Constant Q Transform -- 3 Aligning Techniques -- 3.1 Dynamic Time Warping (DTW) -- 3.2 Levenshtein Distance -- 3.3 The LCS Distance -- 4 Description of the Automatic Evaluation System -- 4.1 Front-End Module -- 4.2 Evaluation Module -- 5 Experiments -- 6 Conclusions and Future Work -- References -- On the Extended Specific Objectivity of Some Pseudo--Rasch Models Applied in Testing Scenarios -- 1 Introduction -- 1.1 Standard Psychometric Models and Specific Objectivity -- 1.2 Generalized Models. 327 $a2 Analysis of the Proposed Models -- 2.1 Behavior of the Extended 6PL Rasch's Model -- 2.2 The Extended 6PL Rasch's Model and Specific Objectivity -- 2.3 An Improved and More Flexible 6PL Model -- 2.4 The Flexible 6PL Model and Specific Objectivity -- 3 Simulation Results -- 3.1 Complete Simulation Process -- 3.2 Partial Simulation Process -- 3.3 Presentation of Experimental Results -- 3.4 Computation of Item's Discriminant -- 3.5 Abilities and Parameters Estimation -- 4 Conclusion -- References -- Algorithms and Machine Learning Techniques in Collaborative Group Formation -- Abstract -- 1 Introduction -- 2 Applied Approches in Collaborative Group Formation -- 3 Analysis and Comparison of the Applied Approaches -- 4 Conclusions -- Acknowledgements -- References -- Biomedical Applications -- An Architecture Proposal Based in Intelligent Algorithms for Motifs Discovery in Genetic Expressions -- Abstract -- 1 Introduction -- 2 Motifs -- 2.1 Deterministic Model -- 2.2 Probabilistic Model -- 2.3 Motif Recognition -- 3 Implementation of the Architecture -- 3.1 Genetic Algorithm -- 3.2 BlastP -- 3.3 Conversion .XML to .FASTA -- 3.4 CD-Hit -- 3.5 MUSCLE -- 3.6 HMMER -- 4 Conclusion and Future Work -- References -- A Kernel-Based Predictive Model for Guillain-Barre? Syndrome -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data -- 2.2 Multiclass Classification -- 2.3 Support Vector Machines (SVM) -- 2.4 Performance Measures -- 3 Experimental Design -- 3.1 10-FCV -- 3.2 Train-Test -- 3.3 C4.5 -- 3.4 SVM Parameter Optimization -- 4 Results and Discussion -- 5 Conclusions -- References -- Feature Selection in Spectroscopy Brain Cancer Data -- 1 Introduction -- 2 Literature Review -- 3 Class-Separability Feature Selection -- 4 Block-Contiguous Feature Selection -- 5 Experimental Settings -- 6 Experimental Results -- 6.1 CSFS Results -- 6.2 BCFS Results. 327 $a6.3 Metabolic Interpretation. 330 $aThe two volume set LNAI 9413 + 9414 constitutes the proceedings of the 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca,. Morelos, Mexico, in October 2015. The total of 98 papers presented in these proceedings was carefully reviewed and selected from 297 submissions. They were organized in topical sections named: natural language processing; logic and multi-agent systems; bioinspired algorithms; neural networks; evolutionary algorithms; fuzzy logic; machine learning and data mining; natural language processing applications; educational applications; biomedical applications; image processing and computer vision; search and optimization; forecasting; and intelligent applications. . 410 0$aLecture Notes in Artificial Intelligence ;$v9414 606 $aArtificial intelligence 606 $aOptical data processing 606 $aHealth informatics 606 $aApplication software 606 $aInformation storage and retrieval 606 $aAlgorithms 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23060 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 615 0$aArtificial intelligence. 615 0$aOptical data processing. 615 0$aHealth informatics. 615 0$aApplication software. 615 0$aInformation storage and retrieval. 615 0$aAlgorithms. 615 14$aArtificial Intelligence. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aHealth Informatics. 615 24$aInformation Systems Applications (incl. Internet). 615 24$aInformation Storage and Retrieval. 615 24$aAlgorithm Analysis and Problem Complexity. 676 $a006.3 702 $aPichardo Lagunas$b Obdulia$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHerrera Alcántara$b Oscar$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aArroyo Figueroa$b Gustavo$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466233703316 996 $aAdvances in Artificial Intelligence and Its Applications$92554689 997 $aUNISA LEADER 00841nam0-2200253 --450 001 9910722901403321 005 20230605105340.0 010 $a978-88-288-2478-7 100 $a20230605d2021----kmuy0itay5050 ba 101 0 $aita 102 $aIT 105 $a 001yy 200 1 $aDalla riforma Biagi al reddito di cittadinanza$el'evoluzione dei modelli di lavoro tra flessibilità e sicurezza, inclusione e politiche attive$fGabriele Fava 210 $aMilano$cGiuffrè Francis Lefebvre$d2021 215 $aX, 217 p.$d24 cm 676 $a344.4501$v23$zita 700 1$aFava,$bGabriele$f<1963- >$01068488 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910722901403321 952 $aVII G 112$b2021/913$fFGBC 959 $aFGBC 996 $aDalla riforma Biagi al reddito di cittadinanza$92554285 997 $aUNINA