Overview

This book constitutes the refereed proceedings of the 19th International Conference on Web Information Systems and Technologies, WEBIST 2023, held in Rome, Italy, during November 15–17, 2023. The 5 full papers and 8 short papers included in this book were carefully reviewed and selected from 77 submissions. The selected papers contribute to the understanding of relevant trends of current research on Web Information Systems and Technologies, including: Human Computer Interaction, Application, Research Project and Internet Technology, UX and User-Centric Systems, Web Programming, Web Tools and Languages, Applications, Research Projects and Web Intelligence, Natural Language Processing, Human Factors, Web Information Filtering and Retrieval and Web Interfaces and Applications.

Full Product Details

Author:   Massimo Marchiori ,  Francisco García Peñalvo
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Volume:   543
ISBN:  

9783031896200

ISBN 10:   3031896203
Pages:   268
Publication Date:   24 June 2025
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available  
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.
Language:   English

Table of Contents

.- Impact of Item Polarity on Semantic Differential Scales in User Experience Measurement. .- An End-User Tool for Supporting Frequent Multisource Web Search Workflows. .- Overview of Web Application Performance Optimization Techniques. .- Interest and Challenges of Students regarding Web and Mobile Technologies. .- SWI (Soft Web Intelligence) Powered by User-Defined Fuzzy Operators and Aggregators. .- Matching Pre-Processed Database Records Using Natural Language Queries on Advertisements. .- Mapping Business Web Applications for Web Automation. .- On the Construction of Text-to-SQL Tools Based on Large Language Models for Real-World Relational Databases. .- Refining Community Boundaries in Bee Swarm Optimization for Enhanced Community Detection in Social Networks.

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