Titlebook: Web Information Systems and Technologies; 16th International C Massimo Marchiori,Francisco José Domínguez Mayo,Jo Conference proceedings 20

GROSS

,: A Language for Soft Querying Features Within GeoJSON Information Layers,actic structure. Currently, querying in an effective way a . document, to extract features of interests, can be hard, for various reasons..In this paper, we propose a domain-specific language named .: it is a high-level tool that hides details of the . format, which enables soft querying of features

depreciate

多余

,: A Language for Soft Querying Features Within GeoJSON Information Layers,actic structure. Currently, querying in an effective way a . document, to extract features of interests, can be hard, for various reasons..In this paper, we propose a domain-specific language named .: it is a high-level tool that hides details of the . format, which enables soft querying of features

一小块

Conference proceedings 20230 and WEBIST 2021, which took place virtually in November 2020 and October 2021, respectively..The 10 full papers from WEBIST 2021 and 1 full paper from WEBIST 2020 presented in this volume were carefully reviewed and selected from originally 48 paper submissions in 2020 and 107 submissions in 2021.

cartilage

,A Comparative Study of Energy Domain Ontologies,gy domain. In this paper, we provide a comprehensive evaluation of semantic reasoning in the energy domain, by evaluating the performance of ten ontologies in terms of different metrics such as load time and run-time performance, discussing how such ontologies can be applicable in case of deployment on devices with constrained resources.

爱社交

,A Comparative Study of Energy Domain Ontologies,gy domain. In this paper, we provide a comprehensive evaluation of semantic reasoning in the energy domain, by evaluating the performance of ten ontologies in terms of different metrics such as load time and run-time performance, discussing how such ontologies can be applicable in case of deployment on devices with constrained resources.

议程

Virtual Testing Environment for Smart Automations in the Internet of Things,we implemented a virtual testing environment where trials are executed in a protected runtime, not confined to a particular location, disengaged from the physical ecosystem. All our tools run locally in a typical mobile machine and may operate in standalone mode without connecting to real smart devi

abduction

,Machine Learning Based Finding of Similar Sentences from French Clinical Notes,grees of semantic similarity between clinical sentences. . is evaluated using traditional evaluation metrics, EDRM (Accuracy in relative distance to the average solution) and Spearman correlation, on standard benchmarks provided in the context of the DEFT 2020 challenge. According to the official re

教育学

Compassionate