AI SearchAdaptive user profile from mobile phone based positionaing using data mining technique (Record no. 1639)
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| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12304918 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.RS-18-08 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Nattawut Yangkhruea |
| 245 10 - TITLE STATEMENT | |
| Title | Adaptive user profile from mobile phone based positionaing using data mining technique |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2018 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 58 leaves : |
| Other physical details | ill. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. RS-18-08 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Remote Sensing and Geographic Information System, School of Engineering and Technology |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M. Sc.) - Asian Institute of Technology, 2018 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | In the Location Based Service Applications it is important to know user's profile in order to provide service to the right person. However, user's profile should build as fast as possible. Trajectory data from a mobile phone device can discover user's profile such as, significant place, transportation mode and daily mobility pattern. First, significant places extraction need to identify related features and calculation then related all features was imported and stored in PostgreSQL database server and was accessed the model by using Psycopg2 module from Python as an adapter. Then Random forest algorithm with hyper-parameter tuning was employed to classify significant place such Home, Work and Other. Secondly, transportation mode detection was analyzed by calculated related features including total point, total distance, total time, minimum velocity, maximum velocity, maximum acceleration, average and velocity. Then Random Forest was applied to classify transportation mode including Car, Motorbike and Train. Third, detecting daily mobility pattern of user and identify the shortest period to detect the main mobility pattern. Splitting data was applied, then generate origins and destination (Ol'i) and calculate the percentage of each Ol). Then visualize Ol) in Gephi was applied to finding the main pattern. Finally calculation the average shortest time and the percentage of main pattern was utilized. Finally, the significant places extraction, transportation mode detection and daily mobility pattern with the minimum time was applied to the test data. The result shown that the minimum time of extracting significant place such as Home is 5 days, Work Place and Other is 7 days. For transportation mode detection, the minimum time is 1 day since it can classify when related features ready. Moreover, the average minimum time of building main daily mobility pattern is 11 days |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Location-based services |
| General subdivision | Social aspects |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Mobile communication systems |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Data mining |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Apichon Witayangkurn, |
| Relator term | Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Sarawut Ninsawat, |
| Relator term | Examination Committee |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Miyazaki, Hiroyuki, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Royal Thai Government, |
| Relator term | Scholarship Donor |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | AIT Fellowship, |
| Relator term | Scholarship Donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Thesis ; |
| Volume/sequential designation | no. RS-18-08 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B22522">http://203.159.5.9/ait-thesis/detail.php?q=B22522</a> |
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| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Cost, normal purchase price | Copy number |
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| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no.RS-18-08 | 30050120880645 | 17/08/2026 | 17/08/2026 | 40-Archives | ||||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no.RS-18-08 | 17/08/2026 | 17/08/2026 | 61-CD-ROM | |||||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 17/08/2026 | AIT Thesis no.RS-18-08 | 30050121012032 | 17/08/2026 | 17/08/2026 | 20-AIT Publication | 50.00 | 1 | ||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 17/08/2026 | AIT Thesis no.RS-18-08 | 30050121012024 | 17/08/2026 | 17/08/2026 | 20-AIT Publication | 50.00 | 2 |