Submit Search
Upload
IRJET- Automatic Database Schema Generator
•
0 likes
•
13 views
IRJET Journal
Follow
https://www.irjet.net/archives/V6/i11/IRJET-V6I11329.pdf
Read less
Read more
Engineering
Report
Share
Report
Share
1 of 5
Download now
Download to read offline
Recommended
Generating requirements analysis models from textual requiremen
Generating requirements analysis models from textual requiremen
fortes
IRJET - Voice based Natural Language Query Processing
IRJET - Voice based Natural Language Query Processing
IRJET Journal
Requirement Analysis - ijcee 2(3)
Requirement Analysis - ijcee 2(3)
IT Industry
IRJET- A Novel Approch Automatically Categorizing Software Technologies
IRJET- A Novel Approch Automatically Categorizing Software Technologies
IRJET Journal
IMPLEMENTATION OF DYNAMIC COUPLING MEASUREMENT OF DISTRIBUTED OBJECT ORIENTED...
IMPLEMENTATION OF DYNAMIC COUPLING MEASUREMENT OF DISTRIBUTED OBJECT ORIENTED...
IJCSEA Journal
Availability Assessment of Software Systems Architecture Using Formal Models
Availability Assessment of Software Systems Architecture Using Formal Models
Editor IJCATR
ThesisProposal
ThesisProposal
Islam Akef Ebeid
Review on Automation Tool for ERD Normalization
Review on Automation Tool for ERD Normalization
IRJET Journal
Recommended
Generating requirements analysis models from textual requiremen
Generating requirements analysis models from textual requiremen
fortes
IRJET - Voice based Natural Language Query Processing
IRJET - Voice based Natural Language Query Processing
IRJET Journal
Requirement Analysis - ijcee 2(3)
Requirement Analysis - ijcee 2(3)
IT Industry
IRJET- A Novel Approch Automatically Categorizing Software Technologies
IRJET- A Novel Approch Automatically Categorizing Software Technologies
IRJET Journal
IMPLEMENTATION OF DYNAMIC COUPLING MEASUREMENT OF DISTRIBUTED OBJECT ORIENTED...
IMPLEMENTATION OF DYNAMIC COUPLING MEASUREMENT OF DISTRIBUTED OBJECT ORIENTED...
IJCSEA Journal
Availability Assessment of Software Systems Architecture Using Formal Models
Availability Assessment of Software Systems Architecture Using Formal Models
Editor IJCATR
ThesisProposal
ThesisProposal
Islam Akef Ebeid
Review on Automation Tool for ERD Normalization
Review on Automation Tool for ERD Normalization
IRJET Journal
Software Engineering Lab Manual
Software Engineering Lab Manual
Neelamani Samal
On the Choice of Models of Computation for Writing Executable Specificatoins ...
On the Choice of Models of Computation for Writing Executable Specificatoins ...
ijeukens
Semantic web based software engineering by automated requirements ontology ge...
Semantic web based software engineering by automated requirements ontology ge...
IJwest
International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)
ijceronline
Improved Presentation and Facade Layer Operations for Software Engineering Pr...
Improved Presentation and Facade Layer Operations for Software Engineering Pr...
Dr. Amarjeet Singh
Lq3620002008
Lq3620002008
IJERA Editor
Ju2517321735
Ju2517321735
IJERA Editor
Performance Evaluation using Blackboard Technique in Software Architecture
Performance Evaluation using Blackboard Technique in Software Architecture
Editor IJCATR
A Methodology To Manage Victim Components Using Cbo Measure
A Methodology To Manage Victim Components Using Cbo Measure
ijseajournal
75752177 ooad-lab-manual-by-n-gopinath-skpit
75752177 ooad-lab-manual-by-n-gopinath-skpit
Subramaniyan94
A DATA EXTRACTION ALGORITHM FROM OPEN SOURCE SOFTWARE PROJECT REPOSITORIES FO...
A DATA EXTRACTION ALGORITHM FROM OPEN SOURCE SOFTWARE PROJECT REPOSITORIES FO...
ijseajournal
A FRAMEWORK STUDIO FOR COMPONENT REUSABILITY
A FRAMEWORK STUDIO FOR COMPONENT REUSABILITY
cscpconf
666 computer technology 7th sem
666 computer technology 7th sem
AbdullahAlMamun146257
Ooad lab manual(original)
Ooad lab manual(original)
dipenpatelpatel
60780174 49594067-cs1403-case-tools-lab-manual
60780174 49594067-cs1403-case-tools-lab-manual
Chitrarasan Kathiravan
Slides chapters 28-32
Slides chapters 28-32
Priyanka Shetty
A hybrid model to detect malicious executables
A hybrid model to detect malicious executables
UltraUploader
Database Engine Control though Web Portal Monitoring Configuration
Database Engine Control though Web Portal Monitoring Configuration
IRJET Journal
IRJET- Software Architecture and Software Design
IRJET- Software Architecture and Software Design
IRJET Journal
IRJET - Automated System for Frequently Occurred Exam Questions
IRJET - Automated System for Frequently Occurred Exam Questions
IRJET Journal
IRJET- Determining Document Relevance using Keyword Extraction
IRJET- Determining Document Relevance using Keyword Extraction
IRJET Journal
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET Journal
More Related Content
What's hot
Software Engineering Lab Manual
Software Engineering Lab Manual
Neelamani Samal
On the Choice of Models of Computation for Writing Executable Specificatoins ...
On the Choice of Models of Computation for Writing Executable Specificatoins ...
ijeukens
Semantic web based software engineering by automated requirements ontology ge...
Semantic web based software engineering by automated requirements ontology ge...
IJwest
International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)
ijceronline
Improved Presentation and Facade Layer Operations for Software Engineering Pr...
Improved Presentation and Facade Layer Operations for Software Engineering Pr...
Dr. Amarjeet Singh
Lq3620002008
Lq3620002008
IJERA Editor
Ju2517321735
Ju2517321735
IJERA Editor
Performance Evaluation using Blackboard Technique in Software Architecture
Performance Evaluation using Blackboard Technique in Software Architecture
Editor IJCATR
A Methodology To Manage Victim Components Using Cbo Measure
A Methodology To Manage Victim Components Using Cbo Measure
ijseajournal
75752177 ooad-lab-manual-by-n-gopinath-skpit
75752177 ooad-lab-manual-by-n-gopinath-skpit
Subramaniyan94
A DATA EXTRACTION ALGORITHM FROM OPEN SOURCE SOFTWARE PROJECT REPOSITORIES FO...
A DATA EXTRACTION ALGORITHM FROM OPEN SOURCE SOFTWARE PROJECT REPOSITORIES FO...
ijseajournal
A FRAMEWORK STUDIO FOR COMPONENT REUSABILITY
A FRAMEWORK STUDIO FOR COMPONENT REUSABILITY
cscpconf
666 computer technology 7th sem
666 computer technology 7th sem
AbdullahAlMamun146257
Ooad lab manual(original)
Ooad lab manual(original)
dipenpatelpatel
60780174 49594067-cs1403-case-tools-lab-manual
60780174 49594067-cs1403-case-tools-lab-manual
Chitrarasan Kathiravan
Slides chapters 28-32
Slides chapters 28-32
Priyanka Shetty
A hybrid model to detect malicious executables
A hybrid model to detect malicious executables
UltraUploader
What's hot
(17)
Software Engineering Lab Manual
Software Engineering Lab Manual
On the Choice of Models of Computation for Writing Executable Specificatoins ...
On the Choice of Models of Computation for Writing Executable Specificatoins ...
Semantic web based software engineering by automated requirements ontology ge...
Semantic web based software engineering by automated requirements ontology ge...
International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)
Improved Presentation and Facade Layer Operations for Software Engineering Pr...
Improved Presentation and Facade Layer Operations for Software Engineering Pr...
Lq3620002008
Lq3620002008
Ju2517321735
Ju2517321735
Performance Evaluation using Blackboard Technique in Software Architecture
Performance Evaluation using Blackboard Technique in Software Architecture
A Methodology To Manage Victim Components Using Cbo Measure
A Methodology To Manage Victim Components Using Cbo Measure
75752177 ooad-lab-manual-by-n-gopinath-skpit
75752177 ooad-lab-manual-by-n-gopinath-skpit
A DATA EXTRACTION ALGORITHM FROM OPEN SOURCE SOFTWARE PROJECT REPOSITORIES FO...
A DATA EXTRACTION ALGORITHM FROM OPEN SOURCE SOFTWARE PROJECT REPOSITORIES FO...
A FRAMEWORK STUDIO FOR COMPONENT REUSABILITY
A FRAMEWORK STUDIO FOR COMPONENT REUSABILITY
666 computer technology 7th sem
666 computer technology 7th sem
Ooad lab manual(original)
Ooad lab manual(original)
60780174 49594067-cs1403-case-tools-lab-manual
60780174 49594067-cs1403-case-tools-lab-manual
Slides chapters 28-32
Slides chapters 28-32
A hybrid model to detect malicious executables
A hybrid model to detect malicious executables
Similar to IRJET- Automatic Database Schema Generator
Database Engine Control though Web Portal Monitoring Configuration
Database Engine Control though Web Portal Monitoring Configuration
IRJET Journal
IRJET- Software Architecture and Software Design
IRJET- Software Architecture and Software Design
IRJET Journal
IRJET - Automated System for Frequently Occurred Exam Questions
IRJET - Automated System for Frequently Occurred Exam Questions
IRJET Journal
IRJET- Determining Document Relevance using Keyword Extraction
IRJET- Determining Document Relevance using Keyword Extraction
IRJET Journal
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET Journal
Named Entity Recognition (NER) Using Automatic Summarization of Resumes
Named Entity Recognition (NER) Using Automatic Summarization of Resumes
IRJET Journal
IRJET - Text Summarizer.
IRJET - Text Summarizer.
IRJET Journal
Algorithm Procedure and Pseudo Code Mining
Algorithm Procedure and Pseudo Code Mining
IRJET Journal
A WEB BASED APPLICATION FOR RESUME PARSER USING NATURAL LANGUAGE PROCESSING T...
A WEB BASED APPLICATION FOR RESUME PARSER USING NATURAL LANGUAGE PROCESSING T...
IRJET Journal
IRJET- Recruitment Chatbot
IRJET- Recruitment Chatbot
IRJET Journal
IRJET - Recommendation System using Big Data Mining on Social Networks
IRJET - Recommendation System using Big Data Mining on Social Networks
IRJET Journal
Running head NETWORK DIAGRAM AND WORKFLOW1NETWORK DIAGRAM AN.docx
Running head NETWORK DIAGRAM AND WORKFLOW1NETWORK DIAGRAM AN.docx
jeanettehully
IRJET- A Detailed Analysis on Windows Event Log Viewer for Faster Root Ca...
IRJET- A Detailed Analysis on Windows Event Log Viewer for Faster Root Ca...
IRJET Journal
Template based framework for rapid fast development of enterprise applications
Template based framework for rapid fast development of enterprise applications
eSAT Journals
Template based framework for rapid fast development
Template based framework for rapid fast development
eSAT Publishing House
Clustering of Big Data Using Different Data-Mining Techniques
Clustering of Big Data Using Different Data-Mining Techniques
IRJET Journal
Development of Information Extraction for Data Analysis using NLP
Development of Information Extraction for Data Analysis using NLP
IRJET Journal
SQL Injection and HTTP Flood DDOS Attack Detection and Classification Based o...
SQL Injection and HTTP Flood DDOS Attack Detection and Classification Based o...
IRJET Journal
IRJET- Deep Web Searching (DWS)
IRJET- Deep Web Searching (DWS)
IRJET Journal
Comparing the performance of a business process: using Excel & Python
Comparing the performance of a business process: using Excel & Python
IRJET Journal
Similar to IRJET- Automatic Database Schema Generator
(20)
Database Engine Control though Web Portal Monitoring Configuration
Database Engine Control though Web Portal Monitoring Configuration
IRJET- Software Architecture and Software Design
IRJET- Software Architecture and Software Design
IRJET - Automated System for Frequently Occurred Exam Questions
IRJET - Automated System for Frequently Occurred Exam Questions
IRJET- Determining Document Relevance using Keyword Extraction
IRJET- Determining Document Relevance using Keyword Extraction
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
Named Entity Recognition (NER) Using Automatic Summarization of Resumes
Named Entity Recognition (NER) Using Automatic Summarization of Resumes
IRJET - Text Summarizer.
IRJET - Text Summarizer.
Algorithm Procedure and Pseudo Code Mining
Algorithm Procedure and Pseudo Code Mining
A WEB BASED APPLICATION FOR RESUME PARSER USING NATURAL LANGUAGE PROCESSING T...
A WEB BASED APPLICATION FOR RESUME PARSER USING NATURAL LANGUAGE PROCESSING T...
IRJET- Recruitment Chatbot
IRJET- Recruitment Chatbot
IRJET - Recommendation System using Big Data Mining on Social Networks
IRJET - Recommendation System using Big Data Mining on Social Networks
Running head NETWORK DIAGRAM AND WORKFLOW1NETWORK DIAGRAM AN.docx
Running head NETWORK DIAGRAM AND WORKFLOW1NETWORK DIAGRAM AN.docx
IRJET- A Detailed Analysis on Windows Event Log Viewer for Faster Root Ca...
IRJET- A Detailed Analysis on Windows Event Log Viewer for Faster Root Ca...
Template based framework for rapid fast development of enterprise applications
Template based framework for rapid fast development of enterprise applications
Template based framework for rapid fast development
Template based framework for rapid fast development
Clustering of Big Data Using Different Data-Mining Techniques
Clustering of Big Data Using Different Data-Mining Techniques
Development of Information Extraction for Data Analysis using NLP
Development of Information Extraction for Data Analysis using NLP
SQL Injection and HTTP Flood DDOS Attack Detection and Classification Based o...
SQL Injection and HTTP Flood DDOS Attack Detection and Classification Based o...
IRJET- Deep Web Searching (DWS)
IRJET- Deep Web Searching (DWS)
Comparing the performance of a business process: using Excel & Python
Comparing the performance of a business process: using Excel & Python
More from IRJET Journal
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
IRJET Journal
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
IRJET Journal
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...
IRJET Journal
Effect of Camber and Angles of Attack on Airfoil Characteristics
Effect of Camber and Angles of Attack on Airfoil Characteristics
IRJET Journal
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...
IRJET Journal
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...
IRJET Journal
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...
IRJET Journal
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...
IRJET Journal
A REVIEW ON MACHINE LEARNING IN ADAS
A REVIEW ON MACHINE LEARNING IN ADAS
IRJET Journal
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...
IRJET Journal
P.E.B. Framed Structure Design and Analysis Using STAAD Pro
P.E.B. Framed Structure Design and Analysis Using STAAD Pro
IRJET Journal
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...
IRJET Journal
Survey Paper on Cloud-Based Secured Healthcare System
Survey Paper on Cloud-Based Secured Healthcare System
IRJET Journal
Review on studies and research on widening of existing concrete bridges
Review on studies and research on widening of existing concrete bridges
IRJET Journal
React based fullstack edtech web application
React based fullstack edtech web application
IRJET Journal
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...
IRJET Journal
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.
IRJET Journal
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...
IRJET Journal
Multistoried and Multi Bay Steel Building Frame by using Seismic Design
Multistoried and Multi Bay Steel Building Frame by using Seismic Design
IRJET Journal
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...
IRJET Journal
More from IRJET Journal
(20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTURE
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...
Effect of Camber and Angles of Attack on Airfoil Characteristics
Effect of Camber and Angles of Attack on Airfoil Characteristics
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...
A REVIEW ON MACHINE LEARNING IN ADAS
A REVIEW ON MACHINE LEARNING IN ADAS
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...
P.E.B. Framed Structure Design and Analysis Using STAAD Pro
P.E.B. Framed Structure Design and Analysis Using STAAD Pro
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...
Survey Paper on Cloud-Based Secured Healthcare System
Survey Paper on Cloud-Based Secured Healthcare System
Review on studies and research on widening of existing concrete bridges
Review on studies and research on widening of existing concrete bridges
React based fullstack edtech web application
React based fullstack edtech web application
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...
Multistoried and Multi Bay Steel Building Frame by using Seismic Design
Multistoried and Multi Bay Steel Building Frame by using Seismic Design
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...
Recently uploaded
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentation
GDSCAESB
Extrusion Processes and Their Limitations
Extrusion Processes and Their Limitations
120cr0395
Porous Ceramics seminar and technical writing
Porous Ceramics seminar and technical writing
rakeshbaidya232001
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
ranjana rawat
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
Call Girls in Nagpur High Profile
main PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfid
NikhilNagaraju
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
Suhani Kapoor
chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learning
misbanausheenparvam
Introduction to Multiple Access Protocol.pptx
Introduction to Multiple Access Protocol.pptx
upamatechverse
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
9953056974 Low Rate Call Girls In Saket, Delhi NCR
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
Call Girls in Nagpur High Profile
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
KurinjimalarL3
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )
Tsuyoshi Horigome
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
9953056974 Low Rate Call Girls In Saket, Delhi NCR
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
purnimasatapathy1234
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
hassan khalil
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
ranjana rawat
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
Call Girls in Nagpur High Profile
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
ranjana rawat
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
srsj9000
Recently uploaded
(20)
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentation
Extrusion Processes and Their Limitations
Extrusion Processes and Their Limitations
Porous Ceramics seminar and technical writing
Porous Ceramics seminar and technical writing
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
(MEERA) Dapodi Call Girls Just Call 7001035870 [ Cash on Delivery ] Pune Escorts
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
Call Girls in Nagpur Suman Call 7001035870 Meet With Nagpur Escorts
main PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfid
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learning
Introduction to Multiple Access Protocol.pptx
Introduction to Multiple Access Protocol.pptx
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
High Profile Call Girls Nagpur Meera Call 7001035870 Meet With Nagpur Escorts
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
APPLICATIONS-AC/DC DRIVES-OPERATING CHARACTERISTICS
SPICE PARK APR2024 ( 6,793 SPICE Models )
SPICE PARK APR2024 ( 6,793 SPICE Models )
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
★ CALL US 9953330565 ( HOT Young Call Girls In Badarpur delhi NCR
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
(ANJALI) Dange Chowk Call Girls Just Call 7001035870 [ Cash on Delivery ] Pun...
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
College Call Girls Nashik Nehal 7001305949 Independent Escort Service Nashik
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
(RIA) Call Girls Bhosari ( 7001035870 ) HI-Fi Pune Escorts Service
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
IRJET- Automatic Database Schema Generator
1.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 11 | Nov 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 3598 Automatic Database Schema Generator Sayali Sant1, Amruthkala Bhat2, Neha Tiwari3, Purva Raut4 1,2,3Student, Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India 4Assistant Professor, Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Automatic Database Schema Generator is a tool that facilitates schema designing from Natural language based textual requirements as an input from the user, thus, automating the process of extracting probable entities and their attributes, identifying primary and foreign keys, etc. and thereby, eliminating time consuming requirement analysis phase in the project developmentlifecycle. Thispaperproposes how Natural language based textual requirements can be analysed to extract the entities from plain text and produce a database schema. Natural language text can tend to be ambiguous due to varied contextualmeaningsassociatedwith the words. In order to reduce this ambiguity, thesystemmakes use of Domain Ontology to identify associated terms in the given context, thus increasing theefficiencyandrichnessof the database hence created. Key Words: Domain ontology, Natural Language Processing, Schema, Entities, Attributes. 1. INTRODUCTION A majority of projects in the industry make use of user data or other related information that needs to be stored in the application systems for further use. A large amount of such information might be later used by the application system itself for further processes or by the service provider. All these linked data are saved in application databasesforlater use. Therefore, designing a database that includes majority of useful information and that does not save redundant or unimportant data is crucial. Currently this process iscarried out manually by repeated analysis of client requirements and multiple iterations ofvalidationfromthe clients.Amajor chunk of Software development time and efforts are to be invested in the initial phases of the cycle for the projecttobe a success. It is important that the fundamental idea of the project cycle be clear and strong enough. Any loophole in this phase will lead to a cascading effect in further stages. Generating the Database Schema for the project from user specifications involves multiple iterations of requirement analysis and rigorous client communications for validation. Projects of all scales make use of this approach irrespective of the type of solution or repetition of business uses. Rapid Application Development processes involve short spanned cycles, where schema generation from analysis result is important, failure of which mayaffectthetimelydeployment of the product. The system aims to create an automatedenvironmentfor analysing textual user requirements and formulating a relevant and client-domain specific database schema by extracting appropriate entities, associated attributes from the analysed text using Domain Ontology. The entities are then mapped according to their relations and key attribute values are identified to compose a full-fledged Relational Schema for the end user. 2. RELATED WORK 2.1. Automatic generation of schema from nested key- value data This system automaticallytransformsself-describing, nested key-value data formats such as JSON, commonly found in NoSQL systems into traditional relational data that can be stored in standard RDBMS. [3] This process includes a schema generation algorithm that discovers relationships across attributes of deformalized datasets to organize them into relational tables. The next process includes a matching algorithm to identify attributes with overlapping entities to merge them together under one entity to reduce data repetition. This system is most useful in cases where databases need to be propagated from a NoSQL system to a relational system thus helping users gain semantic understanding of complex, nested datasets. Figure -1: JSON conversion to RDBMS format Performance: For a large Twitter dataset, the three consecutive phases of the process required 31 hours, 3.6 hours, 31 minutes respectively. In the second phase, it was observed that some
2.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 11 | Nov 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 3599 attribute matches were semantically related; however, a large number of matches were not semantically related and should not have been matched. 2.2. Automatic Relational Schema Extraction from Natural Language RequirementsSpecification Text [1] This methodology deals with automatic construction of the relational database schema by identifying the key attributes from SRS using“rule-basedapproach”.Thesystem architecture and working of each module in the system is as below: Input: The system takes natural language textual requirements as input. Domain Knowledge Elicitor: [1] This module splits the SRS into sentences and tags each word from all the sentences as nouns, verbs, adjectives, etc. using POS (Parts of Speech) tagging. Tagging of words is necessary to chunk the words that form noun phrases or verb phrases. The phrases are classified using simple phrasal grammar. Schema Generator: This module identifies entities, attributes, methods and relationships based on simple rule- based approach from S-V-O pattern: Translating Nouns to Entities, Translating Noun-Noun to entity property according to the position, Translating the lexical verb of a non-personal noun toa methodofthisnoun,TranslatingS-V- O structure to a class diagram with Subject and Object as Entity and verb as relation. Identification of Primary Key (PK) and Foreign Key (FK): [1]A rule based approach is used to identify the primary key attribute from the attributes of all the tables. 3. PROPOSED APPROACH TO BUILD Now we discuss the detailed approach of our proposed system to extract entities and their respective attributes from natural language requirements. It includes mainly following modules. [2] They are accepting the text input and tokenizing it followed by their POS tagging, parsing of ontology represented in OWL, identification of entities and attributes and finally, extraction of key attributes [1]. First module outputs the tagged text using a “Parts of Speech” tagger (POS) from which nouns, noun phrases, and verbs can be identified. Next module is OWL parser which parses the ontology represented in OWL and thus the classes, ObjectProperties and DataProperties are extracted. Now the nouns and noun phrases become the candidate for entities and attributes identification. In the last two steps domain ontology is used to explore the important concepts of the domain. Identificationofentitiesandtheirattributesis followed by extraction of key attributesfortheentities.Thus, at the end we get the desired relational database schema. Figure -2: Architecture of the proposed system Following section describes each module in detail: POS tagger: POS tagger i.e. Part Of Speech tagger will parse the entire text document of user requirements and will tag each word according to its part of speech (e.g. Noun, verb, adjective, adverb, etc.) and extract all the verbs and nouns from it. Now nouns serve as a source of attribute and class identification. OWL Parser: It parses the extracted nouns and verbs using OWL parser. In OWL i.e. Ontology Web Language, domain specific conceptual terms are termed as entities, relationships are termed as ObjectProperty and attributes are represented as DataProperty. So, with the help of OWL Parser these are extracted and stored. Entities and Attributes extractor: Itextractsthecomponents like entities and attributes from the nouns and noun- phrases. Domain ontology is used here to extract contextual entities and attributes. Attributes are specified as DataProperty in OWL. If domain ontology does not contain any information about the nouns and noun phrases under consideration, then the tagged nouns and noun phrases are again processed and semantic similarity is taken into consideration in such cases. Key attribute Extractor: A rule-based approach is used to identify the primary key attribute from the attributes of all
3.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 11 | Nov 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 3600 the tables. Following this, anotherrulebasedapproachhelps in retrieving foreign keys and their associated entities. 4. IMPLEMENTATION The system is implemented using Python Language. The input for the system is Problem statement and Problem domain. The problem statement is in the form of natural text which is then Tokenized, Tagged and Lemmatized using spaCy[8]. spaCy is an open-source software library for advanced Natural Language Processing, written in the programming languages Python and Cython. Based on the input problem domain a suitable Domain Ontology is webscraped and parsed using libraries such as BeautifulSoup and OntoSpy. Nouns from thetaggedproblem statement are classified as Entities and attributes based on lexical and semantic similarity with those extracted after parsing the OWL file that was webscraped based on suitable input Domain ontology. To tackle the ambiguity caused due to use of Natural Language in problem statement and to overcome lexical dissimilarity of common contextual words, the system makes use of Google Dictionary to locate probable synonyms in the problem statement. The schema obtained is then marked with PrimarykeysandForeignkeys according to the relationship between the entities withrule- based algorithms that is explained in detail in the following paragraph. The system aims to provide user flexibility and thus recommends them few extra appropriate and probable entities and attributes that are fit for the problem at hand and can be included in the Schema on need basis. An extra functionality provided by our tool is retrieval of relational database schema if the user wishes to only submit the domain name or theme of the project and not the entire customized problem statement. In this scenario, we simply parse the OWL file of the respective Domain Ontology and provide with the relevant classes, attributes, key attributes and recommended schema related elements. Rule-based Algorithm for determining Primary keys: - FOR EACH attribute IN attribute list of an entity 1. Find attributes with substring “_no/_number/_ID” and String_1=Split and extract the word lying before “_no/_number/_ID” 2. IF String_1 matches with Entity name, THEN it qualifies to be the primary key. 3. ELSE IF Any of the Meanings/Synonyms (that are retrieved through Google dictionary) of String_1 matches with the entity name, THEN it qualifies to be the primary key. 4. ELSE no primary key exists and the entity qualifies to be a weak entity. Rule-based Algorithm for determining Foreign keys: - FOR EACH attribute IN attribute list of an entity 1. Find attributes with substring “_no/_number/_ID” and String_1=Split and extract thewordlyingbefore “_no/_number/_ID” 2. IF String_1 does not match with the Entity name(E) and matches with one of the Entity name in the Entity list(L) THEN it qualifies to be theforeign key of E with the parent Entity being the matchedEntity name from L. 3. ELSE IF Any of the Meanings/Synonyms(that are retrieved through Google dictionary) of String_1 does not match with the Entity name(E) and matches with one of the Entity name in the Entity list(L) THEN it qualifies to be the foreign key of E with the parent Entity being the matched Entity name from L 4. ELSE IF String_1 does not match with the Entity name(E) and matches with the Synonyms of one of the Entity names in the Entity list(L) THEN it qualifies to be the foreign key of E with the parent Entity being the matched Entity name from L 5. ELSE no foreign key exists. Let us consider an example of an “Hospital Management System”. The problem domain entered by the user is “Hospital” and the problem statement entered by the user which is in the natural language based textual format is as follows: - “Patients request forappointmentforanydoctorbyspecifying the doctor_name. and doctor_id. The details of the existing patients like Name, Address, age and gender are retrieved by the system. New patients update their details in the system using a unique patient_id allotted to them before they request for appointment with the help of assistant_name where each assistant can be distinguished based on their distinct Assistant_id. The assistant confirms the appointmentbasedon the availability of free slots for the respective Medical practitioners and the patient isinformed. Assistantmaycancel the appointment at any time.” Firstly, the input text is tokenized, tagged and lemmatized. Secondly, “hospital.owl” i.e. an Ontology based on user entered problem domain is retrieved using web scraping. Thereby, the nouns such as Patients, Doctor, Assistant, slots, etc. are classified as entities and Name, Address, age and gender, doctor_name, etc. areclassifiedasattributeswith the help of the ontology. Ambiguous words like “Doctors” and “Medical Practitioners” are handled further to avoid redundant entities and attributes. The primary key and foreign key of each entity are identified using appropriate rule-based approach. Thus, a database schema is generated.
4.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 11 | Nov 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 3601 The expected output is as follows: - Figure -3: Automatic Database Schema Generator can generate schema from customised problem statement provided by user or from the domain type of user requirement. (For e.g.: User may give a problem statement for Library system as input or only specify ‘Library’ as domain) Figure -4: The textual input and domain of the problem statement is provided as input. Figure -5: The system generates a schema for the given problem statement and identifies Primary keys and Foreign keys. Figure -6: The system also provides some probable schema elements that can be included along with the ones specified by the user to enhance the database. 5. CONCLUSION The Automatic Database Schema Generator tool has been successfully implemented for extracting database schema from natural language textual input problem statement.The tool can analyze words with similar context and integrates the results accordingly. The keys have been identified to denote referential integrity and uniquely identify the entities. An entire repository of commonly used Ontologies proved to be favorable for mapping various attributes to their respective entities. Thus, a well enriched database schema is retrieved with the help of this tool. REFERENCES [1] Automatic Relational Schema Extraction from Natural LanguageRequirementsSpecificationText - S. Geetha and G.S. Anandha Mala, JNTU Hyderabad Andhra Pradesh, India, Head / CSE, St. Joseph’sCollegeof Engineering, India, IDOSI Publications, 2014 DOI: 10.5829/idosi.mejsr.2014.21.03.21475 Patients Doctor Assistant Name Doctor_name Assistant_name Gender Specialization Degree Age Degree Address Address Address Age Age Patient_id (Primary key) Doctor_id (Primary key) Assistant_id (Primary key)
5.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 11 | Nov 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 3602 [2] Domain Ontology Based Class Diagram Generation From Functional Requirements Jyothilakshmi M S and Philip Samuel Information Technology, School of Engineering, Cochin University of Science and Technology, Kochi-22 Kerala India International Journal of Computer Information Systems and Industrial Management Applications. ISSN 2150-7988 Volume 6 (2014) pp. 227 [3] Automatic Generation of Normalized Relational Schemas from Nested Key-Value Data Michael DiScala, Yale University Daniel J. Abadi, Yale University [4] Class diagram extraction from textual requirements using Natural language processing (NLP) techniques Mohd Ibrahim Al-Qaoud, Rodina Ahmad Department of Software Engineering, Faculty of Computer Science and Information technology, University of Malaya, Malaysia [5] Auto-generation of Class Diagram from Free-text Functional Specifications and Domain Ontology Xiaohua Zhou, Nan Zhou [6] NLP based Object Oriented Analysis and Design from Requirement Specification Subhash K.Shinde LT College of Engg. Navi Mumbai Varunakshi Bhojane PIIT New Panvel, Navi Mumbai International Journal of Computer Applications (0975 – 8887) Volume 47– No.21, June 2012. [7] Natural Language ProcessingElizabethD.LiddySyracuse University, liddy@syr.edu [8] Fensel D. (2001) Ontologies. In: Ontologies. Springer, Berlin, Heidelberg, Print ISBN 978-3-662-04398-1 [8] spaCy:https://spacy.io/Websites https://protege.stanford.edu/publications/ontology_dev elop ment/ontology101-noy-mcguinness.html
Download now