HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONS
Big data has a huge impact on urban planning and cities morphology. Big data is utilized to appraise the requirements of the shared transport structure, by focusing on funding and portability plans inside the key cities. The research provides a recommendation-making system (RMS) focused on suggestin...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Faculty of Applied Management, Economics and Finance – MEF, Belgrade, University Business Academy in Novi Sad
2022-08-01
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| Series: | Journal of Process Management and New Technologies |
| Subjects: | |
| Online Access: | https://drive.google.com/file/d/1zy1Jzwdmh_LwVc3J_yKt4wCJW4dWIyyq/view?usp=sharing |
| _version_ | 1797823266260254720 |
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| author | Mesbaul Haque Sazu Sakila Akter Jahan |
| author_facet | Mesbaul Haque Sazu Sakila Akter Jahan |
| author_sort | Mesbaul Haque Sazu |
| collection | DOAJ |
| description | Big data has a huge impact on urban planning and cities morphology. Big data is utilized to appraise the requirements of the shared transport structure, by focusing on funding and portability plans inside the key cities. The research provides a recommendation-making system (RMS) focused on suggesting transport methods to automobile consumption by detailing a huge volume of transport methods information originating from various products. The research focuses on the utilization of big data to come down with shared transport, and presents a structural understanding for gathering, combining, aggregating, incorporating, disseminating, and controlling information from numerous origins. Information extraction methods are utilized, allowing the evaluation of both organized big data, that follows developed benchmarks like CRISP-DM, and disorganized, readily offered big data. Investigational information has been gathered from a representative of phones and automatic vehicle location devices in the region. The suggested RMS allowed to examine the temporal and spatial scope of shared transport facilities, and suggested plans to enhance the transportation.
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| first_indexed | 2024-03-13T10:21:33Z |
| format | Article |
| id | doaj.art-1dd2fd44376841309de44ff5827141e4 |
| institution | Directory Open Access Journal |
| issn | 2334-735X 2334-7449 |
| language | English |
| last_indexed | 2024-03-13T10:21:33Z |
| publishDate | 2022-08-01 |
| publisher | Faculty of Applied Management, Economics and Finance – MEF, Belgrade, University Business Academy in Novi Sad |
| record_format | Article |
| series | Journal of Process Management and New Technologies |
| spelling | doaj.art-1dd2fd44376841309de44ff5827141e42023-05-20T09:37:03ZengFaculty of Applied Management, Economics and Finance – MEF, Belgrade, University Business Academy in Novi SadJournal of Process Management and New Technologies2334-735X2334-74492022-08-01103-4921https://doi.org/10.5937/jpmnt10-38013HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONSMesbaul Haque Sazu0Sakila Akter Jahan1Case Western Reserve University, Cleveland, Ohio, USAIndependent University, Bangladesh, Dhaka, BangladeshBig data has a huge impact on urban planning and cities morphology. Big data is utilized to appraise the requirements of the shared transport structure, by focusing on funding and portability plans inside the key cities. The research provides a recommendation-making system (RMS) focused on suggesting transport methods to automobile consumption by detailing a huge volume of transport methods information originating from various products. The research focuses on the utilization of big data to come down with shared transport, and presents a structural understanding for gathering, combining, aggregating, incorporating, disseminating, and controlling information from numerous origins. Information extraction methods are utilized, allowing the evaluation of both organized big data, that follows developed benchmarks like CRISP-DM, and disorganized, readily offered big data. Investigational information has been gathered from a representative of phones and automatic vehicle location devices in the region. The suggested RMS allowed to examine the temporal and spatial scope of shared transport facilities, and suggested plans to enhance the transportation. https://drive.google.com/file/d/1zy1Jzwdmh_LwVc3J_yKt4wCJW4dWIyyq/view?usp=sharingdecision-makingpublic transportationbig data analytics |
| spellingShingle | Mesbaul Haque Sazu Sakila Akter Jahan HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONS Journal of Process Management and New Technologies decision-making public transportation big data analytics |
| title | HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONS |
| title_full | HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONS |
| title_fullStr | HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONS |
| title_full_unstemmed | HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONS |
| title_short | HIGH EFFICIENCY PUBLIC TRANSPORTATION SYSTEM: ROLE OF BIG DATA IN MAKING RECOMMENDATIONS |
| title_sort | high efficiency public transportation system role of big data in making recommendations |
| topic | decision-making public transportation big data analytics |
| url | https://drive.google.com/file/d/1zy1Jzwdmh_LwVc3J_yKt4wCJW4dWIyyq/view?usp=sharing |
| work_keys_str_mv | AT mesbaulhaquesazu highefficiencypublictransportationsystemroleofbigdatainmakingrecommendations AT sakilaakterjahan highefficiencypublictransportationsystemroleofbigdatainmakingrecommendations |