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  • Home
  • About Us
  • Research
  • Program
    • WG1 Education for IMS
    • WG2 Human Resource Exchange
    • WG3 Workshops and Conferences
    • WG4 MOOC Based Training
    • WG5 QA & Feedback
  • Schedule
  • Achievements
  • Contact

Engineering Support Layer

HomeEngineering Support Layer

Research

  • UI Management Layer
  • Engineering Support Layer
  • Knowledge Acquisition and Interferencing
  • Data Acquisition and Persistence
  • Service Integration Layer

Engineering Support Layer

Objective

The main objective of knowledge Engineering Tool is to facilitate the physicians for creating shareable and interoperable knowledge. It provides evidence and dialogue based knowledge engineering systems to facilitate the physicians to create, verify, validate and manage the knowledge base using multimodal knowledge resources and divers communication ways. 

 

Features

The primary feature of knowledge Engineering Tool to evolve the knowledge of a medical platform to generate up to date recommendation to the end users using state-of-the-art knowledge and natural language conversation technologies. It has the following features. 

 

1. To facilitate domain experts with base-line knowledge acquired from existing practice data sets and their experiences and heuristics.

2. To facilitate the physician for physicians for verifying and validating the extracted knowledge from structured and unstructured data. 

3. To equip  the platform with Intelligent Knowledge Engineering Tool (Rule Editor and Rule Compiler) to author shareable and interoperable knowledge base.

4. To facilitate users (patients and physicians) to dialog with system using multimodal (text, voice, and image) dialog interface. 

5. To provide execution environment with Interface Engine Supporting Rule-based Reasoner and case based reasoning.

6. To facilitate ontologicasl modeling for Intent identification from the dialog between user and system

7. To design SPARQL queries to interact with Ontological Model for text/speech based dialogue process.

 

Uniqueness & Contribution

1. Semantic Reconciliation model to generate interoperable knowledge

2. Automatic generation of Medical Logic Module

3. Facilitates MLM (Medical Logic Module) based knowledge base maintenance

4. Enlist Highly Relavant Evidence against a user provided natural language query 

5. Select High Quality evidentiary documents based on novel statistiscal models

6. Intent recognition 

7. Context Aware Dialogue Manegement 

 

 

Detailed Architecture

 

 

 

The UCLab. at the Kyung Hee University is consisted of more than 30 Post-doc, Ph.D and Master students, working on research projects under the supervision of Prof. Sungyoung Lee, who studied in the field of ubiquitous systems.

Primary Address

Office of Prof. Sungyoung Lee(Room 313) Dept. of Computer Engineering, Kyung Hee University Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, Korea

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