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AKTU Intelligent Database System (BAI053) Syllabus PDF – B.Tech 3rd Year
Intelligent Database System BAI053
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Official AKTU syllabus of Intelligent Database System (BAI053) for B.Tech 3rd Year – 3 credits, L-T-P 3-0-0. Read the unit-wise course content, course outcomes, evaluation pattern and recommended books online, or download the PDF.
Syllabus — Intelligent Database System
Download PDFBAI053 · 3 credits · L-T-P 3-0-0
Course Outcomes
At the end of course , the student will be able to:
| CO 1 | Understand the concepts of Intelligent database. | K 2 |
| CO 2 | Make study of the Database installation then create the database with user and apply SQL. | K , K 2 3 |
| CO 3 | Understand the concepts of knowledge-based systems and apply with AI | K , K 2 3 |
| CO 4 | Design and create the small applications | K , K 5 6 |
| CO 5 | Analyze and Implement for various real-time applications in Intelligent Database System | K , K 4 5 |
Course Content
L-T-P: 3-0-0
| Unit | Topic | Proposed Lecture |
|---|---|---|
| I | Introduction to IDBS- Informal definition of the domain - General characteristics of IDBSs - Data models and the relational data model - A taxonomy of intelligent database systems - Guidelines for using intelligent database systems. Practical Component: (a) Install the LAMP (b) Configure and setup the Connection between back end & Front End. | 08 |
| II | Semantic Data Models Nested and semantic data models – Introduction - The nested relational model - Semantic models - Hyper-semantic data models - Object-oriented approaches to semantic data modeling – Objectoriented database systems - Basic concepts of a core object-oriented data model - Comparison with other data models - Query languages and query processing - Operational aspects – Systems – The ODMG standard - The object-relational data model - Java and databases – Conclusions – Active database systems - Basic concepts – Issues – Architectures - Research relational prototypes—the Starburst Rule System - Commercial relational approaches. Practical Component: (a) Design & create the DB user in database. (b) Using SQL - create sample DB for Language –DDL, DML and DCL. (c) Create sample java/PHP pages with database access. | 08 |
| III | Knowledge-Based Systems- AI Ccontext Characteristics and classification of the knowledge-based systems – Introduction - The resolution principle - Inference by inheritance – Conclusion - Deductive database systems - Basic concepts - DATALOG language - Deductive database systems and logic programming systems—differences - Architectural approaches - Research prototypes - Updates in deductive databases - Integration of deductive database and object database technologies - Constraint databases - Conclusions. Practical Component: 1. Working on basic commands on datalog 2. Practice on projection and Selection in datalog 3. Write a program that uses + and - from racket/base as external queries using DATALOG language | 08 |
| IV | Advanced Knowledge-Based Systems Introduction - Architectural solutions - The 'general bridge' solution - Extending a KBS with components proper to a DBMS - The 'tight coupling' approach – Conclusion - Advanced solutions: Introduction - A 'knowledge level' approach to the interaction with an IAS- TELOS - a language for implementing very large 'integral approach' systems- The CYC project - Other projects based on a 'conceptual representation' approach - Lexical approaches to the construction of large KBs. Practical Component: Implement the techniques to manage knowledge-based systems. | 08 |
| V | Applications in IDBS Introduction - Temporal databases - Basic concepts - Temporal data models - Temporal query languages – Ontologies -Ontology theoretical foundations - Environments for building ontologies - Structured, semi-structured and unstructured data - Multimedia database - Semi-structured data - Mediators – Motivation – Architecture - Application of mediators to heterogeneous systems –Proposals - Multi-Agents systems - Main issues in designing a multi-agent system - Open problems. Internet indexing and retrieval - Basic indexing methods - Search engines or meta-searchers – Internet spiders - Data mining - Data mining tasks - Data mining tools - Medical and legal information systems - Medical information systems - Legal information systems – Conclusions. Practical Component: 1. Implement the temporal databases. 2. Design and develop a project using medical information system. | 08 |
Text Books
- Elisa Bertino, Barbara Catania, GianPieroZarri, “Intelligent Database Systems”,Collection ACM Press.
- Ngoc ThanhNguyen, RadoslawKatarzyniak,andShyi-MingChen (Eds.), "Advances in Intelligent Information andDatabase Systems ", Springer, 2010.
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