Tactical crime analysis using clustering on San Francisco crime data | |
| Author | Ponnuru, Anitha |
| Call Number | AIT RSPR no.IM-17-05 |
| Subject(s) | Data mining--Computer programs Cluster analysis--Data processing |
| Note | A research submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Information Management, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Research studies project report ; no. IM-17-05 |
| Abstract | In the digital era, police forces have access to quickly expanding sources of information. The enormous increase in the amount of available data has made the use of data mining techniques essential in finding important patterns. This research, on the data collected from kaggle competition,San Francisco Crime Classification, will take combinations of type of crime and time to determine locations where it is more likelytooccur. Thiswillhelpinplanningpreventivemeasures. Thoughthekagglecompetition expected the participants to determine the type of crime occurring given they have knowledge about the time and location, in this paper the outcome is slightly changed since many studies have been done on the before mentioned problem.To predict the outcome i.e. given the type of crime and time, at which location(s) it’s more likely to occur, in this study the technique used will be k-means clustering . ForperformingK-meansclusteringWekadataminingtoolwasused.Alsothedifferenttypesof crimes were analyzedon the basis ofdays in a week and graphsare providedto understand the relation between the rates of crime and the day it is happening on. In the results the location(s) of the most prominent crimes and time are given which will help the police forces to take preventive measures. |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Research studies project report ; no. IM-17-05 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information Management (IM) |
| Chairperson(s) | Sumanta, Guha; |
| Examination Committee(s) | Vatcharaporn Esichaikul;Chutiporn Anutariya; |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship; |
| Degree | Research studies project report (M. Eng.) - Asian Institute of Technology, 2017 |