Skip to search
Skip to main content
Catalog
Help
Feedback
Your Account
Library Account
Bookmarks
(
0
)
Search History
Search in
Keyword
Title (keyword)
Author (keyword)
Subject (keyword)
Title starts with
Subject (browse)
Author (browse)
Author (sorted by title)
Call number (browse)
search for
Search
Advanced Search
Bookmarks
(
0
)
Princeton University Library Catalog
Start over
Cite
Send
to
SMS
Email
EndNote
RefWorks
RIS
Printer
Bookmark
Advances in computational intelligence. Part II. : 21st Mexican international conference on artificial intelligence, MICAI 2022, Monterrey, Mexico, October 24-29, 2022, proceedings / edited by Obdulia Pichardo Lagunas, Juan Martínez-Miranda, and Bella Martínez Seis.
Format
Book
Language
English
Published/Created
Cham, Switzerland : Springer, [2022]
©2022
Description
1 online resource (402 pages)
Availability
Available Online
Springer Nature - Springer Computer Science eBooks 2022 English International
Springer Nature - Springer Lecture Notes in Computer Science eBooks
Details
Subject(s)
Computational intelligence
—
Congresses
[Browse]
Computational intelligence
[Browse]
Editor
Martínez-Miranda, Juan
[Browse]
Martínez Seis, Bella
[Browse]
Pichardo Lagunas, Obdulia
[Browse]
Series
Lecture Notes in Computer Science
[More in this series]
Lecture Notes in Computer Science ; v.13613
[More in this series]
Bibliographic references
Includes bibliographical references and index.
Source of description
Description based on print version record.
Contents
Intro
Preface
Conference Organization
Contents - Part II
Contents - Part I
Natural Language Processing
Urdu Named Entity Recognition with Attention Bi-LSTM-CRF Model
1 Introduction
2 Related Work
2.1 Rule-Based Techniques
2.2 Statistical Techniques
2.3 Hybrid Techniques
3 Our Proposal
3.1 Embedding Layer
3.2 Bi-LSTM Module
3.3 Attention Layer
3.4 Encoder Layer
3.5 Conditional Random Field (CRF)
3.6 Prediction Layer
4 Experimental Setup
4.1 Data
4.2 Experiments
4.3 Evaluation Metrics
5 Results
6 Conclusions
References
Impact Evaluation of Multimodal Information on Sentiment Analysis
2 Dataset
3 Method
3.1 Text Processing and Feature Extraction
3.2 Emoji Processing
3.3 Text in Image Detection
3.4 Image Sentiment Label
3.5 Feature Fusion
3.6 Classification Algorithm
4 Experimental Results
5 Conclusions and Future Work
.26em plus .1em minus .1emImproving Neural Machine Translation for Low Resource Languages Using Mixed Training: The Case of Ethiopian Languages
1.1 High vs Low Resource Languages
3 Dataset
4 Methodology
4.1 Data Pre-processing
4.2 Model
5 Experiments and Results
5.1 Experiments
5.2 Dataset Split
5.3 Results
6 Conclusions and Future Work
Machine Translation of Texts from Languages with Low Digital Resources: A Systematic Review
2 Method
2.1 Phase 1: Documentary Search
2.2 Phase 2: Description of Selection Criteria
2.3 Phase 3: Analysis and Categorization
2.4 Phase 4: Discussion
3 Conclusions
Comparison Between SVM and DistilBERT for Multi-label Text Classification of Scientific Papers Aligned with Sustainable Development Goals
2 Related Work.
2.1 Problem Transformation Method and Classification Algorithm
2.2 Transfer Learning Model
3 Methodology
3.1 Framework for Multi-label Text Classification
4 Model Experiments
4.1 Dataset
4.2 Data Preprocessing
4.3 Models Building
4.4 Model Evaluation
5 Results and Discussion
6 Conclusion and Future Work
A Hybrid Methodology Based on CRISP-DM and TDSP for the Execution of Preprocessing Tasks in Mexican Environmental Laws
2 Methodology Conceptualization for the Preprocessing of Legislative Documents
2.1 Methodology Description
3 Methodology Implementation for the Preprocessing of Legislative Documents
3.1 Judiciary of Mexico
3.2 Text Preprocessing Use Case for Environmental Laws
4 Validation of the Results
4.1 Business Understanding Deliverables
4.2 Data Understanding Deliverables
4.3 Data Preparation Deliverables
4.4 Experimental Process Deliverables
4.5 Experimental Process Results
5 Conclusions
News Intention Study and Automatic Estimation of Its Impact
2 State of the Art
2.1 Difference of This Proposal with Respect to the State of the Art Presented Above
3 Solution Development
3.1 Description of the Solution
3.2 Scientific Novelty
3.3 Evaluation
4 Experiments and Results
Evaluation of a New Representation for Noise Reduction in Distant Supervision
3.1 Dataset
3.2 Baseline of Representation Learning Methods
3.3 Unsupervised Representation Learning Methods
3.4 Anomaly Detection Methods
3.5 Experimental Design
4 Experiments and Evaluation
Automatic Identification of Suicidal Ideation in Texts Using Cascade Classifiers
1 Introduction.
2 Related Works
3 Proposed Method
3.1 Datasets
3.2 Weighing of Terms
3.3 Cascade Classification
4 Experimentation and Results
Web Crawler and Classifier for News Articles
2 Web Crawling and Corpus Creation
3 Classifier
4 Web Application
Sentiment Analysis in the Rest-Mex Challenge
2 Corpus and Task Description
3.1 Lexicon-Based Approach
3.2 Machine Learning Approach
4.1 Experiments with the Lexicon-Based Approach
4.2 Experiments with the Machine Learning Approach
A Bibliometric Review of Methods and Algorithms for Generating Corpora for Learning Vector Word Embeddings
2 Methodology
2.1 Methods
2.2 Materials
3 Results
3.1 Publications and Citations by Year
3.2 Top Conferences and Journals
3.3 Top Institutions and Funding Organizations
3.4 Top Influential Publications
3.5 Top Countries by Publications
4 Discussion
5 Conclusion
Evaluating the Impact of OCR Quality on Short Texts Classification Task
3.1 Selection of Classification Categories
3.2 Obtaining OCRed Text
3.3 The Human Typed Text and Its Approximations
3.4 Train/Test Split
4 Classification Approaches
4.1 Fuzzy Substring Search
4.2 CNN
4.3 BERT
4.4 RoBERTa
5.1 Evaluation Metrics
5.2 Experiments
Techniques for Generating Language Learning Resources: A System for Generating Exercises for the Differentiation of Literal and Metaphorical Context
2 Characteristics of Automatic Generation Systems for Learning.
2.1 NLP Tasks at Automatic Generation Systems for Language Learning
2.2 Creation Sources
2.3 Technical and Methodological Aspects of Automatic Generation Systems for Learning
2.4 Text Preprocessing
3 An Automatic Generation System for Learning the English Language: Literal Language and Metaphorical Language
3.1 Corpus Selection
3.2 System Development: General Preprocessing
3.3 System Development: Exercises
4 Results
4.1 The Exercises Generated and Their Validation
Exploratory Data Analysis for the Automatic Detection of Question Paraphrasing in Collaborative Environments
2 Theorical Framework
3 State of the Art
3.1 Scientific Novelty and Difference with the State of the Art
4 Solution Development
4.1 Initial EDA
4.2 Preprocessing
4.3 Feature Extraction
4.4 Analysis of Preprocessed Data
4.5 Classifier Models
4.6 Model Comparison
Best Paper Award
Diachronic Neural Network Predictor of Word Animacy
2 Data and Method
4 Case Study
Sequential Models for Sentiment Analysis: A Comparative Study
2 Literature Review
3 Experimental Setup
4 Results and Discussion
Intelligent Applications and Robotics
Analysis of Procedural Generated Textures for Video Games Using a CycleGAN
2.1 Procedural Content Generation
2.2 Generative Adversarial Networks
2.3 CycleGAN
3 Proposed Approach
4.1 CycleGAN Training Details
4.2 CycleGAN Results
4.3 Emotional Data Collection
4.4 Emotional Results
References.
Vibration Analysis of an Industrial Motor with Autoencoder for Predictive Maintenance
1.1 A Subsection Sample
2 Background
3.1 Materials and Test Bench Construction
6 Conclusions and Future Work
Modeling and Simulation of Swarm of Foraging Robots for Collecting Resources Using RAOI Behavior Policies
2 Foraging Behavior
3 Swarm Features
3.1 Robot Mathematical Model
3.2 Limitations of Sensory Capacity of Robots
3.3 Local Behavior Rules
4 Simulation Environment
6 Conclusion
Data-Driven Adaptive Force Control for a Novel Soft-Robot Based on Ultrasonic Atomization
2 Actuation and Soft-Robot Design
2.1 Ultrasonic Atomization
2.2 Rapid Actuator Design
2.3 Mini Soft-Robot Design
3 Intelligent Control
3.1 Neuro-Fuzzy Architecture
3.2 Adaptation Algorithm
Data-driven-modelling and Control for a Class of Discrete-Time Robotic System Using an Adaptive Tuning for Pseudo Jacobian Matrix Algorithm
2 Data-driven Model for Discrete-Time System
2.1 Equivalent Model Stability Analysis
2.2 Neuro-fuzzy Network and Adaptive Step Parameter
3 Control Law
Retrieval-based Statistical Chatbot in a Scientometric Domain
2.1 Natural Language Processing
2.2 Intent Classificaiton and Entity Extraction
2.3 Data Labeling
2.4 Model Training
2.5 Scientometric Indicator Identification
2.6 Natural Language Transformation into Cypher Query
2.7 Chatbot Deployment
3 Results and Discussion
3.1 Goal Completion Rate
3.2 Survey Evaluation
4 Conclusion
Red Light/Green Light: A Lightweight Algorithm for, Possibly, Fraudulent Online Behavior Change Detection.
Show 216 more Contents items
ISBN
3-031-19496-9
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
Read more...
Other views
Staff view
Ask a Question
Suggest a Correction
Report Harmful Language
Supplementary Information