Cov19VaxKB: A Web-based Integrative COVID-19 Vaccine Knowledge Base

Chatbots or conversational agents are computer programs that interact with users using natural language through artificial intelligence in a way that the user thinks he is having dialogue with a human. One of the main limits of chatbot technology is associated with the construction of its local knowledge base. A conventional chatbot knowledge base is typically hand constructed, which is a very time-consuming process and may take years to train a chatbot in a particular field of expertise. This chapter extends the knowledge base of a conventional chatbot beyond its local knowledge base to external knowledge source Wikipedia. This has been achieved by using Media Wiki API to retrieve information from Wikipedia when the chatbot's local knowledge base does not contain the answer to a user query. To make the conversation with the chatbot more meaningful with regards to the user's previous chat sessions, a user-specific session ability has been added to the chatbot architecture. An open source AIML web-based chatbot has been modified and programmed for use in the health informatics domain. The chatbot has been named VDMS – Virtual Diabetes Management System. It is intended to be used by the general community and diabetic patients for diabetes education and management.

Download Full-text

Effective Project Management Using Web-Based System with Integrated Knowledge Base

Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part I - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-319-46583-8_8 ◽

2016 ◽

pp. 93-101

Author(s):

František Babič ◽

Barbora Čurová

Keyword(s):

Project Management ◽

Knowledge Base ◽

Web Based ◽

Web Based System ◽

Integrated Knowledge

Download Full-text

LEA: Software System for Multimedia and Virtual-Reality Web-Based Education and Training

Volume 3: 26th Computers and Information in Engineering Conference ◽

10.1115/detc2006-99292 ◽

2006 ◽

Cited By ~ 1

Author(s):

Tamer M. Wasfy

Keyword(s):

Virtual Reality ◽

Knowledge Base ◽

Education And Training ◽

Software System ◽

Web Based ◽

Fully Integrated ◽

Step Process ◽

Base Engine ◽

2D And 3D ◽

And Training

LEA (Learning Environments Agent) is a web-based software system for advanced multimedia and virtual-reality education and training. LEA consists of three fully integrated components: (1) unstructured knowledge-base engine for lecture delivery; (2) structured hierarchical process knowledge-base engine for step-by-step process training; and (3) hierarchical rule-based expert system for natural-language understanding. In addition, LEA interfaces with components which provide the following capabilities: 3D near photo-realistic interactive virtual environments; 2D animated multimedia; near-natural synthesized text-to-speech, speech recognition, near-photorealistic animated virtual humans to act as instructors and assistants; and socket-based network communication. LEA provides the following education and training functions: multimedia lecture delivery; virtual-reality based step-by-step process training; and testing capability. LEA can deliver compelling multimedia lectures and content in science fields (such as engineering, physics, math, and chemistry) that include synchronized: animated 2D and 3D graphics, speech, and written/highlighted text. In addition, it can be used to deliver step-by-step process training in a compelling near-photorealistic 3D virtual environment. In this paper the LEA system is presented along with typical educational and training applications.

Download Full-text

Knowledge Base Commons (KBCommons) v1.0: A multi OMICS' web-based data integration framework for biological discoveries

2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) ◽

10.1109/bibm.2018.8621369 ◽

2018 ◽

Cited By ~ 2

Author(s):

Shuai Zeng ◽

Zhen Lyu ◽

Siva Ratna Kumari Narisetti ◽

Dong Xu ◽

Trupti Joshi

Keyword(s):

Data Integration ◽

Knowledge Base ◽

Web Based ◽

Integration Framework

Download Full-text

BUILDING A KNOWLEDGE BASE FOR IMPLEMENTING A WEB-BASED COMPUTERIZED RECOMMENDATION SYSTEM

International Journal of Artificial Intelligence Tools ◽

10.1142/s0218213007003552 ◽

2007 ◽

Vol 16 (05) ◽

pp. 793-828 ◽

Cited By ~ 10

Author(s):

JUAN D. VELÁSQUEZ ◽

VASILE PALADE

Keyword(s):

Knowledge Base ◽

Web Site ◽

Web Mining ◽

Recommendation System ◽

The Internet ◽

Web Pages ◽

Web Based ◽

Web Logs ◽

Mining Tools ◽

The Web

Understanding the web user browsing behaviour in order to adapt a web site to the needs of a particular user represents a key issue for many commercial companies that do their business over the Internet. This paper presents the implementation of a Knowledge Base (KB) for building web-based computerized recommender systems. The Knowledge Base consists of a Pattern Repository that contains patterns extracted from web logs and web pages, by applying various web mining tools, and a Rule Repository containing rules that describe the use of discovered patterns for building navigation or web site modification recommendations. The paper also focuses on testing the effectiveness of the proposed online and offline recommendations. An ample real-world experiment is carried out on a web site of a bank.

Download Full-text

PERANCANGAN SISTEM PAKAR UNTUK MENGIDENTIFIKASI GANGGUAN PADA TANAMAN JAMBU AIR MENGGUNAKAN METODE CERTAINTY FACTOR

Journal of Applied Science and Technology ◽

10.30659/jast.1.01.1-5 ◽

2021 ◽

Vol 1 (01) ◽

pp. 1

Author(s):

Ahmat Yusuf ◽

Bagus Satrio Waluyo Poetro

Keyword(s):

Expert System ◽

Knowledge Base ◽

Programming Language ◽

Crop Yields ◽

Certainty Factor ◽

Crop Failure ◽

Web Based ◽

Pests And Diseases ◽

The Core ◽

Central Java

The state of Indonesia, especially in the area of Central Java, is one of the largest producers of water guava. Some farmers rely on the results of guava cultivation as the basis for the family's economy because the guava harvest is quite promising. However, in certain seasons, water guava plants are often attacked by various kinds of pest and disease season disturbances. So that it can reduce crop yields or even cause crop failure. To overcome this problem, fast and precise action is needed so that the guava plant is protected from various kinds of pests and diseases. The method of developing an expert system for disturbance in water guava plants is the best solution in order to identify disturbances in water guava plants as early as possible. The method used in this expert system is the certainty factor method. With this method, several experts are needed to provide data related to disturbances in water guava plants. The expert system for guava plant disorders is designed using a web-based PHP programming language. In designing the knowledge base, which is the core of this system, is made dynamically to make it easier to add new data.

Download Full-text

Ontologies and Fine-Grained Control Over Sharing of Engineering Modeling Knowledge in a Web Based Engineering Environment

Computers and Information in Engineering ◽

10.1115/imece2005-81373 ◽

2005 ◽

Cited By ~ 1

Author(s):

Neelima Kanuri ◽

Ian R. Grosse ◽

Jack C. Wileden ◽

Wei-Shan Chiang

Keyword(s):

Knowledge Sharing ◽

Knowledge Base ◽

Automatic Generation ◽

Base System ◽

Engineering Analysis ◽

Analysis Model ◽

Web Based ◽

Technical Report ◽

Engineering Modeling ◽

Base Application

Within the knowledge modeling community the use of ontologies in the construction of knowledge intensive systems is now widespread. Ontologies are used to facilitate knowledge sharing, reuse, agent interoperability and knowledge acquisition. We have developed an ontology for representing and sharing engineering analysis modeling (EAM) knowledge in a web-based environment and implemented these ontologies into a computational knowledge base system, called ON-TEAM, using Prote´ge´1. In this paper we present new object-oriented methods that operate on the EAM knowledge base to perform specific tasks. One such method is the creation of a flat technical report that describes the properties or class relationships of an engineering modeling analysis class and/or the modeling knowledge involved in the development of a specific engineering analysis model. This method is a JAVA application that accesses the EAM knowledge base application using the Prote´ge´ application programming interface. It presents the user a graphical user interface for selecting the EAM class or specific analysis model instance and then exports the appropriate knowledge to a text file to form the basis of a technical report. Secondly, a method controlling knowledge access and sharing is under development which allocates permissions to portions of the knowledge base according to accessibility permissions. This method controls as efficiently as possible fine grain knowledge sharing. Both the methods acting together enable automatic generation of recipient-specific technical reports based on the recipient’s security permissions, customized knowledge viewing, and customized knowledge exporting through various knowledge exchange formats such as XML Walsh [1], RDF Klyne [2], etc. Finally, implementation of these methods and our EAM knowledge base application as components within commercial web-based distributed software architecture is presented.

Download Full-text