Library assistant tool
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This is a Library Assistant Tool for Library's Book Management which recommended books for the reader, suggest librarian add a specific category or writers book and also recommended removing unpopular books from the library and statistical analysis(multi-variable linear regression, analytical hierarchy process, and page rank algorithm), checking accuracy by the cross-validation and its visualization.
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Library assistant tool
- 1. Supervised by: Kishan Kumar Ganguly Lecturer, Institute of Information Technology University of Dhaka Project Name: Library AssistantTool 1 Software Project Lab - 1 Author Name: Md. Rakib Trofder BSSE 2ndYear
- 3. Basic Concepts Library Assistant Tool This tool will help readers to select popular books and, assist librarian to add or remove books. 3
- 6. Reader Readers Recommended Books For Reader Writer wise Type wise Time wise Shelf wise 6
- 8. Librarian Librarian Recommended for adding books Organize Books Recommended for removing books Showing all books information 8
- 9. Tool’s Functionality Analysis Library Assistant Tool Implement 3 different methods CrossValidation for Checking Accuracy Visualize output through charts Show data distribution Through 7 value Statistics 9
- 10. Tool’s Functionality Analysis Library Assistant Tool Implement 3 different methods Multi-variable Linear Regression Page Rank Algorithm Analytical Hierarchy Process 10
- 11. Multi-variable Linear Regression Multi-variable Regression This is a method used to measure the degree to which more than one independent variable (predictors) and one dependent variable (responses) are linearly related and assumption the outcome value. Y = B0 +B1X1+ B2X2 + B3X3 11 Y= book priority, X1= borrow priority X2= time priority, X3= price priority
- 12. Analytical Hierarchy Process Analytical Hierarchy Process Analytical Hierarchy Process, where there are many criteria and sub- criteria and then calculate dependencies and give the final results for each object 12 Criteria Price High Medium Low Deman d High Highly Medium Lowly Medium Low Type Latest New Newly Old Old Oldest Time Uponna sh Kobita Sci Fi Religion Kishore Uponna sh Others
- 13. Page RankAlgorithm Page Rank Algorithm PageRank Algorithm is an algorithm to rank objects by calculating the relationships among all others objects. 13 Book34 • Uponnash • Himu Rimande • Humayon Ahmed • 7 times Book99 • Kisore Uponnash • Kazi Maymur Hossen • 7 times Book 235 • Shishu Samite • Dusto Cele • Jafar Iqbal • 10 times Book 212 • Shishu Sahitto • Boka Rajar • Humayon Ahmed • 12 times
- 14. Page RankAlgorithm Page Rank Algorithm PageRank Algorithm is an algorithm to rank objects by calculating the relationships among all others objects. 14 Book34 • Uponnash • Himu Rimande • Humayon Ahmed • 7 times Book99 • Kisore Uponnash • Duronto • Kazi Maymur Hossen • 7 times Book 235 • Shishu Samite • Dusto Cele • Jafar Iqbal • 10 times Book 212 • Shishu Sahitto • Boka Rajar • Humayon Ahmed • 12 times
- 15. Tools & Implementations Java Programming Language Java FX Framework 120+ Java Classes 88% Source Code 37000 + Lines of Code 1300+ git commits Tool s 15
- 16. Project Design Tool Reader Default Recommendation Type Wise Self Wise Time Wise Writer Wise Reader based Recommendation Sign Up Login Library Book Based Recommendation Librarian Book adding Recommendation Book removing Recommendation Book Information Type of Books Demand of Books Timeline of Books Number of Books System Process Description Process Implementation Multi-variable Regression Analytical Hierarchy Process Page Rank Algorithm Process Analysis Cross Validation CV Description CV Visualization Training Set Testing Set Training Testing Set CV Implementation 7 Value Methods Comperison 16
- 17. References My Repository: https://github.com/rakib3004/SPL1 Library’s Book Information from: https://www.facebook.com/khilkhetpathagar/ MultiVariable Regression: https://brilliant.org/wiki/multivariate-regression/ Analytical Hierarchy Process: https://en.wikipedia.org/wiki/Analytic_hierarchy_process_%E2%80%93_car_example Page RankAlgorithm: https://en.wikipedia.org/wiki/PageRank CrossValidation: https://towardsdatascience.com/cross-validation-explained-evaluating-estimator-performance- e51e5430ff85 https://www.analyticsvidhya.com/blog/2018/05/improve-model-performance-cross- validation-in-python-r/ JavaFXTutorial: https://tutorials.jenkov.com/javafx/index.html 17
- 18. 18 Thank You