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Information Management and Big Data: 4th Annual International Symposium, SIMBig 2017, Lima, Peru, September 4-6, 2017, Revised Selected Papers (Communications in Computer and Information Science, 795)

معرفی کتاب «Information Management and Big Data: 4th Annual International Symposium, SIMBig 2017, Lima, Peru, September 4-6, 2017, Revised Selected Papers (Communications in Computer and Information Science, 795)» نوشتهٔ Juan Antonio Lossio-Ventura (editor), Hugo Alatrista-Salas (editor)، منتشرشده توسط نشر Springer International Publishing در سال 2018. این کتاب در فرمت pdf، زبان انگلیسی ارائه شده است.

This book constitutes the refereed proceedings of the 4th Annual International Symposium on Information Management and Big Data, SIMBig 2017, held in Lima, Peru, in September 2017. The 10 revised full papers presented were carefully reviewed and selected from 71 submissions. The papers address issues such as Data Science, Big Data, Data Mining, Natural Language Processing, Text Mining, Information Retrieval, Machine Learning, Semantic Web, Ontologies, Web Mining, Knowledge Representation and Linked Open Data, Social Web and Web Science, Information Visualization. Preface Reference Organization Contents Parallelization of Conjunctive Query Answering over Ontologies 1 Introduction 2 The Enhanced Most Specific Concept (MSC) Method 2.1 Basic MSC Method 2.2 MSC Computation with Assertion Cycles 2.3 Syntactic Conditions 2.4 Parallelization of the MSC Method 3 Conjunctive Query Answering and SPARQL 4 Experimental Evaluation 4.1 MSC Method Accuracy 4.2 Parallelization 4.3 SPARQL Query Accuracy 5 Discussion and Future Work 6 Conclusion References Could Machine Learning Improve the Prediction of Child Labor in Peru? 1 Introduction 2 Theoretical Background 2.1 Logit Model 2.2 Artificial Neural Networks 2.3 Child Labor in Peru 3 Research Method 3.1 Measurement Model 3.2 Data Collection and Analysis 4 Results 4.1 Logit Results 4.2 Neural Network Results 4.3 Technique Comparison 5 Discussion References Impact of Entity Graphs on Extracting Semantic Relations 1 Introduction 2 Related Works 3 Community Graph of Entities 3.1 Definition of the Graph 3.2 Construction of the Community Graph 4 Relation Validation 4.1 Graph-Based Features 4.2 Linguistic Features 5 Data 5.1 Data for Computing Features 5.2 Data for Training and Testing the Models 6 Results and Discussion 6.1 Results on the Relation Validation Task 6.2 Results of Knowledge Base Population Task 7 Conclusion References Predicting Invariant Nodes in Large Scale Semantic Knowledge Graphs 1 Introduction 2 Related Work 3 Data 4 Methods 5 Results 5.1 Type Analysis 6 Application to Natural Language Generation 7 Conclusions References Privacy-Aware Data Gathering for Urban Analytics 1 Introduction 2 Related Works 3 Data Gathering Framework 4 Datasets 5 Dataset Statistics 6 Sentiment Analysis of Crimes in Peru 7 Conclusion References Purely Synthetic and Domain Independent Consistency-Guaranteed Populations in SHIQ(D) 1 Introduction 2 Synthetic Data Generation 2.1 Concept Assertions 2.2 Role Assertions 2.3 Data Assertions 3 Performances of JPOT 3.1 Domain TBox 3.2 Domain Rbox 3.3 Generated Aboxes 4 Related Works 5 Conclusion References Language Identification with Scarce Data: A Case Study from Peru 1 Introduction 2 Peruvian Indigenous Languages 3 Related Work 4 Corpus Development 5 Language Identification Model 5.1 Standard Supervised Learning 5.2 Deep Supervised Learning 6 Statistical Comparison Test 7 Results and Discussions 8 Conclusions and Future Work References A Multi-modal Data-Set for Systematic Analyses of Linguistic Ambiguities in Situated Contexts 1 Disambiguation and Structural Prediction 2 Linguistic Ambiguities in Situated Contexts 2.1 LASC Data-Set:V1 3 Multi-modal Parsing 3.1 A Proof-of-Concept Study 4 Discussion References Community Detection in Bipartite Network: A Modified Coarsening Approach 1 Introduction 2 Fundamentals 2.1 Basic Definitions 2.2 Multilevel Optimization 3 Community Detection Based on Multilevel Approach by Using One-Mode Projection 4 Experimental Results and Analysis 5 Conclusions References Reconstructing Pedestrian Trajectories from Partial Observations in the Urban Context 1 Introduction 2 Background Concepts and Related Work 2.1 Trajectory Segmentation 2.2 Map Matching 2.3 Inference 3 Reconstructing Uncertain Pedestrian Trajectories 3.1 Trajectory Segmentation 3.2 Map Matching 3.3 Inference 4 Experiments 4.1 Data Sets 4.2 Experimental Results 5 Conclusion References Author Index
دانلود کتاب Information Management and Big Data: 4th Annual International Symposium, SIMBig 2017, Lima, Peru, September 4-6, 2017, Revised Selected Papers (Communications in Computer and Information Science, 795)