Ontology‐Based Case Retrieval in an E‐Mental Health Intelligent Information System

Kaoura, Georgia; Kovas, Konstantinos; Boutsinas, Basilis

doi:10.1002/9781119641391.ch8

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Considering all aforementioned problems, a reasonable research in machine translation, automatic ontology learning from unstructured text, and the semantic information annotation and extraction is required to excel in the field of information retrieval. Kaoura G et al [7] introduces a new approach for the confrontment of ASD. The fact that a user may enter the system from wherever he/she desires (either from home during his free time and for free or from any other place) is added value to the application, helping practically to the health management problem.…”

Section: Literature Surveymentioning

confidence: 99%

OntoImVid-ontology based semantic image/video processing

Lakshmi

Sankari

2022

ijhs

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The rapid increase in the available amount of video data is creating a growing demand for efficient methods for understanding and managing it at the semantic level. Domain ontology is used to define high level semantic concepts and their relations in the context of the examined domain. A low-level features and video content analysis algorithms are integrated into the ontology to enrich video semantic analysis. OWL is used for the ontology description. Rules in Description Logic are defined to describe how features and algorithms for video analysis should be applied according to different perception content and low-level features. OntoImVid structure is created from both image and video semantic analysis results. Proposed OntoImVid combines the image and Video retrieval in same semantic retrieval technique in efficient manner.

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Section: Literature Surveymentioning

confidence: 99%