Proceedings Article10.1109/ISCES.2018.8340520
Intelligent database interface techniques using semantic coordination
Tareq Abed Mohammed,Shaymaa Alhayli,Saad Albawi,Adil Deniz Duru +3 more
- 01 Jan 2018
8
TL;DR: This paper proposes a general design for an intelligent database interface which implies that this interface can be utilized with any database and proves the efficiency of the proposed method in intelligent database system.
read more
Abstract: More and more the use of artificial intelligence and data mining techniques established in many fields to solve the problem of classification. This paper consider most new database applications request smart interface to improve effective collaborations in the middle of database and the clients. The most open interfaces for databases must be clever and ready to comprehend characteristic dialect expressions. The overall aim of this study is to look at the importance of using data mining techniques with artificial intelligence in algorithms and applications. We propose a general design for an intelligent database interface. Furthermore, a genuine usage of such a framework which can be connected to any database. One of the fundamental attributes of this interface is space, freedom, which implies that this interface can be utilized with any database. Another aspect of this framework is that it is easy setup. The intelligent interface utilizes semantic coordinating procedure to change natural language query to Structured Query Language (SQL) by depending lexicon and set of creation guidelines. The lexicon comprises semantics sets for tables and sections. The query model is executed and the outcomes are introduced to the client. This interface was initially tested utilizing Supplier-Parts database by using JAVA and the result proves the efficiency of the proposed method in intelligent database system.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A Novel Software Engineering Approach Toward Using Machine Learning for Improving the Efficiency of Health Systems
TL;DR: The novel approach sheds light on its features and allows users to study and analyze the user requirements and determine both the function of objects related to the system and the machine learning algorithms that must be applied to the dataset.
Hybrid solution of challenges future problems in the new generation of the artificial intelligence industry used operations research industrial processes
Tareq Abed Mohammed,Mohammed N. Qasim,Oguz Bayat +2 more
- 05 Apr 2021
TL;DR: In this paper, the authors provide an international forum for quick articles that describe the practical application of artificial intelligence in all areas of mechanical engineering, and present the architecture of the industrial laboratory and the challenges associated with the use of Artificial Intelligence in industrial processes.
2
The Integration of Artificial Intelligence Into Database Systems(AI-DB Integration Review)
Unuriode O. Austine,Durojaiye M. Olalekan,Yusuf Y. Babatunde,Okunade O. Lateef +3 more
- 07 Oct 2023
TL;DR: In this review, different concepts were discussed by emphasizing some key areas like the design of Intelligent Database Interfaces, Learnable databases, and Smart Query, which geared us to investigate how AI enhances database efficiency by optimizing query performance, automating routine management tasks, and fortifying data security.
1
References
•Book
Data Mining: Practical Machine Learning Tools and Techniques
Ian H. Witten,Eibe Frank,Mark Hall +2 more
- 25 Oct 1999
TL;DR: This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
25.4K
The WEKA data mining software: an update
TL;DR: This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.
Database resources of the National Center for Biotechnology Information
David L. Wheeler,Deanna M. Church,Ron Edgar,Scott Federhen,Wolfgang Helmberg,Thomas L. Madden,Joan Pontius,Gregory D. Schuler,Lynn M. Schriml,Edwin Sequeira,Tugba O. Suzek,Tatiana Tatusova,Lukas Wagner +12 more
TL;DR: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website.
•Posted Content
Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition
TL;DR: This work presents a framework for the recognition of natural scene text that does not require any human-labelled data, and performs word recognition on the whole image holistically, departing from the character based recognition systems of the past.