Ranking the locations and predicting future crime occurrence by
retrieving news from different Bangla online newspapers
- URL: http://arxiv.org/abs/2305.10698v1
- Date: Thu, 18 May 2023 04:19:26 GMT
- Title: Ranking the locations and predicting future crime occurrence by
retrieving news from different Bangla online newspapers
- Authors: Jumman Hossain, Rajib Chandra Das, Md. Ruhul Amin, Md. Saiful Islam
- Abstract summary: We have come up with an approach which can give an approximation to people about the safety of a specific location.
Our approach relies on different online Bangla newspapers for crawling the crime data.
- Score: 2.3979112009934163
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: There have thousands of crimes are happening daily all around. But people
keep statistics only few of them, therefore crime rates are increasing day by
day. The reason behind can be less concern or less statistics of previous
crimes. It is much more important to observe the previous crime statistics for
general people to make their outing decision and police for catching the
criminals are taking steps to restrain the crimes and tourists to make their
travelling decision. National institute of justice releases crime survey data
for the country, but does not offer crime statistics up to Union or Thana
level. Considering all of these cases we have come up with an approach which
can give an approximation to people about the safety of a specific location
with crime ranking of different areas locating the crimes on a map including a
future crime occurrence prediction mechanism. Our approach relies on different
online Bangla newspapers for crawling the crime data, stemming and keyword
extraction, location finding algorithm, cosine similarity, naive Bayes
classifier, and a custom crime prediction model
Related papers
- Exploring The Relationship Between Road Infrastructure and Crimes in
Memphis, Tennessee [91.3755431537592]
The pothole and crime data are collected from Memphis Data Hub between 2020 and 2022.
The crime data report various crimes in the Memphis area, which contain the location, time, and type of the crime.
The pothole data is part of the Open 311 data, which contains information of different infrastructure projects.
arXiv Detail & Related papers (2022-12-02T03:52:35Z) - Crime Prediction using Machine Learning with a Novel Crime Dataset [0.0]
Bangladesh has a high crime rate due to poverty, population growth, and many other socio-economic issues.
For law enforcement agencies, understanding crime patterns is essential for preventing future criminal activity.
This paper introduces a novel crime dataset that contains temporal, geographic, weather, and demographic data about 6574 crime incidents of Bangladesh.
arXiv Detail & Related papers (2022-11-03T01:55:52Z) - If it Bleeds, it Leads: A Computational Approach to Covering Crime in
Los Angeles [79.4098551457605]
We present a machine-in-the-loop system that covers individual crimes by learning the prototypical coverage archetypes from classical news articles on crime to learn their structure.
We hope our work can lead to systems that use these components together to form the skeletons of news articles covering crime.
arXiv Detail & Related papers (2022-06-14T19:06:13Z) - Spatial-Temporal Hypergraph Self-Supervised Learning for Crime
Prediction [60.508960752148454]
This work proposes a Spatial-Temporal Hypergraph Self-Supervised Learning framework to tackle the label scarcity issue in crime prediction.
We propose the cross-region hypergraph structure learning to encode region-wise crime dependency under the entire urban space.
We also design the dual-stage self-supervised learning paradigm, to not only jointly capture local- and global-level spatial-temporal crime patterns, but also supplement the sparse crime representation by augmenting region self-discrimination.
arXiv Detail & Related papers (2022-04-18T23:46:01Z) - American Hate Crime Trends Prediction with Event Extraction [0.0]
The FBI's Uniform Crime Reporting (UCR) Program collects hate crime data and releases statistic report yearly.
Recent research mainly focuses on hate speech detection in social media text or empirical studies on the impact of a confirmed crime.
This paper proposes a framework that first utilizes text mining techniques to extract hate crime events from New York Times news, then uses the results to facilitate predicting American national-level and state-level hate crime trends.
arXiv Detail & Related papers (2021-11-09T04:30:20Z) - The effect of differential victim crime reporting on predictive policing
systems [84.86615754515252]
We show how differential victim crime reporting rates can lead to outcome disparities in common crime hot spot prediction models.
Our results suggest that differential crime reporting rates can lead to a displacement of predicted hotspots from high crime but low reporting areas to high or medium crime and high reporting areas.
arXiv Detail & Related papers (2021-01-30T01:57:22Z) - Crime Prediction Using Multiple-ANFIS Architecture and Spatiotemporal
Data [0.0]
We have used several Fuzzy Inference Systems (FIS) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to predict the type of crime that is highly likely to occur at a certain place and time.
arXiv Detail & Related papers (2020-11-07T19:57:30Z) - Fine-Grained Crowd Counting [59.63412475367119]
Current crowd counting algorithms are only concerned with the number of people in an image.
We propose fine-grained crowd counting, which differentiates a crowd into categories based on the low-level behavior attributes of the individuals.
arXiv Detail & Related papers (2020-07-13T01:31:12Z) - Crime Prediction Using Spatio-Temporal Data [8.50468505606714]
Supervised learning technique is used to predict crimes with better accuracy.
The proposed system is feed with a criminal-activity data set of twelve years of San Francisco city.
arXiv Detail & Related papers (2020-03-11T16:19:19Z) - Exploring Spatio-Temporal and Cross-Type Correlations for Crime
Prediction [48.1813701535167]
We perform crime prediction exploiting the cross-type and-temporal correlations of urban crimes.
We propose a coherent framework to mathematically model these correlations for crime prediction.
Further experiments have been conducted to understand the importance of different correlations in crime prediction.
arXiv Detail & Related papers (2020-01-20T00:34:53Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.