Exploring Data Mining Applications for Crime Rate Prediction

This report examines the application of data mining techniques in predicting crime rates. It begins by defining data mining and its various types, such as clustering, association, and classification, emphasizing their roles in processing and interpreting large datasets. The report highlights the necessity of data mining in crime rate prediction, noting its ability to identify patterns, correlations, and anomalies that aid in solving crimes efficiently. It discusses the advantages, including faster crime solving and improved resource allocation, as well as the disadvantages, such as privacy concerns and data bias. The study also explores how data mining assists in crime rate prediction in the UK, referencing specific methodologies and applications within the UK's criminal justice system. The research employs a literature review methodology, analyzing various studies and articles to provide a comprehensive overview of the subject. Ultimately, the report concludes that data mining is a valuable tool for crime prevention and law enforcement, with recommendations for responsible and ethical implementation.

Application of data
mining in crime rate
prediction

Abstract
Using a vast variety of techniques, one could use this records to increase revenues, reduce
fees, improve client relationships, lessen risks and more. Data mining is the manner of
information information via cleaning raw facts, locating styles, developing fashions, and testing
those fashions. It includes records, device learning, and database structures. data mining is an
activity of identifying patterns, correlation and anomalies within wide range of data sets in order
to predict results. Through using data mining technique, businesses can avail information for
reducing crime, increasing revenue, reducing risk and improving customer relationship. Police
department mainly use data mining tools in crime rate prediction and understand data through
cleaning raw data, creating models and finding patterns. Crime is certainly one of transcendent
and disturbing part of our preferred public. Ordinary first-rate variety of violations are
completed, those successive wrongdoings have made the existences of ordinary citizens
worrying. Thus, keeping the crime from taking place is a essential challenge. In the new time, it
is visible that automated reasoning has tested its significance in nearly all of the subject and
wrongdoing expectation is one in every of them. However, it's far expected to keep the
exceptional information set of the wrongdoing that has happened as this information may be
utilized for destiny reference. The potential to foresee the wrongdoing that may take region in
future can assist the regulation authorization offices in forestalling the wrongdoing earlier than it
takes place.

Contents
Abstract............................................................................................................................................2
INTRODUCTION...........................................................................................................................4
Research Objectives...............................................................................................................4
Research Questions................................................................................................................5
Rationale for the research.......................................................................................................5
LITERATURE REVIEW................................................................................................................5
What is the concept of data mining along with its types?......................................................5
Why it is necessary to use data mining technique in crime rate prediction?..........................6
What are the advantages and disadvantages of data mining in crime rate prediction?..........9
How data mining helps in prediction of crime rate in UK?.................................................11
Methodology..................................................................................................................................14
Discussion and Findings................................................................................................................16
Conclusion and Recommendations................................................................................................23
Limitations of the research.............................................................................................................25
REFERENCES..............................................................................................................................27

INTRODUCTION
Data mining is the method of finding anomalies, styles and correlations within massive facts
units to are expecting outcomes (Agarwal and et.al., 2020). Using a vast variety of techniques,
one could use this records to increase revenues, reduce fees, improve client relationships, lessen
risks and more. Data mining is the manner of information information via cleaning raw facts,
locating styles, developing fashions, and testing those fashions. It includes records, device
learning, and database structures. Data mining is a manner to extract know-how out of
commonly large statistics units; in other words it is an method to discover hidden relationships
amongst facts through using synthetic intelligence methods. The information which is availed
through data mining helps in reducing crime as it helps in identifying the culprits faster and also
find the areas that are affected by crime. Criminology is one of the maximum important fields for
applying information mining. It encompasses the system of coming across hidden styles and
relationships in large amounts of information. This allows for making accurate and dependable
predictions of destiny activities, primarily based on the identity and characterization of these
styles and trends in historical records. The respective research will explain the concept of data
mining along with its types, why it is necessary to use data mining technique in crime rate
prediction and the advantages and disadvantages of data mining in crime rate prediction. It is
these structures that are responsible for storing information that comes out of the smallest of
transactions into the database. So, statistics related to sale, purchase, human capital control, and
other transactions are saved in database servers by means of OLTP systems. Now, pinnacle
executives need access to statistics primarily based on statistics to base their decisions on. This is
where on line analytical processing or OLAP systems enter the picture. Data warehouses and
different OLAP systems are built an increasing number of due to this very need of or top
executives. We don’t most effective want data however additionally the analytics associated with
it to make better and more profitable selections. OLTP and OLAP structures work in tandem.
Research Objectives
 To determine the concept of data mining along with its types.
 To analyze the necessity to use data mining technique in crime rate prediction.
 To identify the advantages and disadvantages of data mining in crime rate prediction.
 To analyze how data mining helps in prediction of crime rate in UK.

Research Questions
 What is the concept of data mining along with its types?
 Why it is necessary to use data mining technique in crime rate prediction?
 What are the advantages and disadvantages of data mining in crime rate prediction?
 How data mining helps in prediction of crime rate in UK?
Rationale for the research
The primary rationale for the respective research is to enhance my overall knowledge about
the concept of application of data mining in crime rate prediction. This is because I will be able
to develop new skills as well as implement the same in any further researches that I undertake.
This will help in conducting the research effectively as well as gathering appropriate data in an
effective manner. Apart from this, another reason for choosing this research is that it is linked
with the course that I am currently undertaking. Hence, I want to ensure that I implement all the
learnings from that I gain from the respective research, I implement in the future. This is because
it will not only help me in completing the respective research in an effective manner, but also, I
will be able to ensure that the findings as well as conclusions of the research are relevant as well
as valid and reliable.
LITERATURE REVIEW
What is the concept of data mining along with its types?
According to Lin, Chen and Yu (2017), data mining is an activity of identifying patterns,
correlation and anomalies within wide range of data sets in order to predict results. Through
using data mining technique, businesses can avail information for reducing crime, increasing
revenue, reducing risk and improving customer relationship. Police department mainly use data
mining tools in crime rate prediction and understand data through cleaning raw data, creating
models and finding patterns (Alam, and et.al., 2021). Data mining mainly includes machine
learning, statistics and database system. There are various types of data mining such as
clustering, association, data cleaning, data visualization, classification, machine learning,
prediction and neural networks. It has been identified that Data mining can be utilized to show
crime detection issues. The thought here is to attempt to catch long stretches of human
experience into PC models through data mining. Crimes are a social aggravation and cost our
general public sincerely in more than one way. Any research that can help in tackling crimes

quicker will pay for itself. These types of data mining helps in managing the data, improve data
quality, make data readably understand to individuals, classify crime on the basis of crime and
also help in identifying all sorts of data patterns. Each types of data mining have its own method
and ways for managing the data.
Criminology is a method that pursuits to identify crime characteristics (Brayne, 2020).
Actually crime evaluation consists of exploring and detecting crimes and their relationships with
criminals. The excessive extent of crime datasets and additionally the complexity of relationships
between these types of records have made criminology the perfect area for making use of records
mining techniques. Identifying crime characteristics is step one for developing in addition
evaluation. The expertise this is gained from facts mining processes is a very useful device that
can help and guide police forces. Data mining is the method of coming across actionable data
from massive sets of information. Data mining makes use of mathematical analysis to derive
styles and developments that exist in records.
Why it is necessary to use data mining technique in crime rate prediction?
As per the opinion of Sangani, Sampat and Pinjarkar (2019), it is important to use data
mining techniques in crime rate prediction as it helps in solving the crime in effective and
efficient manner. Through data mining technique, the crime department can also avail productive
results when applied on crime datasets (Chamikara and et.al., 2020). The information which is
availed by data mining technique helps in producing significant outcomes from crime report
datasets. It is used in crime rate prediction for exploring and detecting crime and their
relationship with criminals. The approaches of data mining are very useful for police forces.
Process of data mining is based on algorithms to analyse and extract information due to which
the hidden pattern and relationship within the data is automatically discovers. By using data
mining technique, police department can gather crude information and separate data which can
be applied to make expectation in numerous true circumstances. The methods of data mining are
used to estimate the future wrongdoing patterns of UK. It also helps in assuming the significant
part in criminal concealment and wrongdoing control in various nations. Data mining also helps
in extracting valuable data from enormous datasets and also maintains the connection between
the traits of data.
Data mining helps in fixing the crimes quicker and this technique gives exact effects while
carried out on crime dataset, the records acquired from the facts mining strategies can assist the

police branch. Produce crucial outcomes from crime file datasets. The very step in examine of
crime is crime analysis (Fouad and et.al., 2020). Crime analysis and prediction is a scientific
approach for figuring out the crime. This machine can expect area that have high chance for
crime occurrences and visualize crime prone place. Using the concept of information mining we
are able to extract previously unknown, useful records from an unstructured statistics. Businesses
in recent times are amassing information at a completely putting rate. The sources of this big
records circulate are various. It could come from credit card transactions, publicly available
client records, data from banks and monetary establishments, as well as the statistics that
customers should provide simply to apply and down load an software on their laptops, cell
telephones, capsules, and computers. It isn't always easy to store such big quantities of statistics.
So, many relational database servers are being continuously constructed for this purpose. Online
transactional protocol or OLTP systems also are being advanced to keep all that into special
database servers. OLTP structures play a crucial role in assisting groups feature smoothly.
The Descriptive Data-Mining Tasks can also be further divided into four types that are as
follows: Clustering Analysis (Islam and et.al., 2021). Association Rules Analysis. Sequence
Discovery Analysis. Data mining is the process of searching large sets of data to look out for
patterns and trends that can't be found using simple analysis techniques. Data mining has several
types, including pictorial data mining, text mining, social media mining, web mining, and audio
and video mining amongst others. Data mining is the process of discovering actionable
information from large sets of data. Data mining uses mathematical analysis to derive patterns
and trends that exist in data. Businesses these days are collecting data at a very striking rate. The
sources of this enormous data stream are varied. It could come from credit card transactions,
publicly available customer data, data from banks and financial institutions, as well as the data
that users have to provide just to use and download an application on their laptops, mobile
phones, tablets, and desktops (Marmo, 2021). It is not easy to store such massive amounts of
data. So, many relational database servers are being continuously built for this purpose. Online
transactional protocol or OLTP systems are also being developed to store all that into different
database servers. OLTP systems play a vital role in helping businesses function smoothly. Data
mining is the method of discovering actionable records from large sets of records. Data mining
uses mathematical evaluation to derive styles and tendencies that exist in information.
Businesses these days are amassing statistics at a completely putting rate. The sources of this

good sized data stream are numerous. It ought to come from credit card transactions, publicly
available client facts, records from banks and financial institutions, as well as the statistics that
customers need to provide just to apply and down load an utility on their laptops, cellular phones,
capsules, and desktops.
The facts which is availed via data mining approach enables in producing substantial
effects from crime document datasets. It is used in crime fee prediction for exploring and
detecting crime and their courting with criminals. The tactics of statistics mining are very useful
for police forces. Process of statistics mining is based totally on algorithms to analyse and extract
records due to which the hidden sample and dating within the information is routinely discovers.
By the use of information mining method, police branch can gather crude records and separate
information which can be carried out to make expectation in numerous proper occasions. The
methods of statistics mining are used to estimate the future wrongdoing styles of UK. It
additionally allows in assuming the sizable element in criminal concealment and wrongdoing
control in numerous nations. Data mining also helps in extracting precious information from
significant datasets and also continues the relationship among the trends of facts.
It is these systems that are responsible for storing data that comes out of the smallest of
transactions into the database. So, data related to sale, purchase, human capital management, and
other transactions are stored in database servers by OLTP systems. Now, top executives need
access to facts based on data to base their decisions on. This is where online analytical
processing or OLAP systems enter the picture. Data warehouses and other OLAP systems are
built more and more because of this very need of or top executives. We don’t only need data but
also the analytics associated with it to make better and more profitable decisions. OLTP and
OLAP systems work in tandem.
Data mining is the process of coming across actionable facts from big sets of facts. Data
mining uses mathematical evaluation to derive patterns and tendencies that exist in information.
Typically, those styles can not be discovered by using traditional information exploration
because the relationships are too complex or due to the fact there is too much statistics. The idea
of data mining has been with us seeing that lengthy before the digital age. The idea of making
use of records to information discovery has been round for centuries, beginning with guide
formulation for statistical modeling and regression analysis. In the Nineteen Thirties, Alan
Turing delivered the idea of a normal computing system that might carry out complicated

computations. This marked the rise of the electromechanical laptop and with it, the ever-
increasing explosion of virtual information that keeps to this very day. It is these structures that
are responsible for storing information that comes out of the smallest of transactions into the
database. So, statistics related to sale, purchase, human capital control, and other transactions are
saved in database servers by means of OLTP systems. Now, pinnacle executives need access to
statistics primarily based on statistics to base their decisions on. This is where on line analytical
processing or OLAP systems enter the picture. Data warehouses and different OLAP systems are
built an increasing number of due to this very need of or top executives. We don’t most effective
want data however additionally the analytics associated with it to make better and more
profitable selections. OLTP and OLAP structures work in tandem.
Data has end up part of every side of business and lifestyles (Usman and et.al., 2021).
Companies today can harness facts mining programs and system getting to know for everything
from enhancing their income procedures to decoding financials for funding purposes. As a result,
information scientists have end up essential to corporations all around the global as corporations
are searching for to reap bigger dreams than ever earlier than. Data mining can solution business
questions that had been traditionally not possible to reply due to the fact they have been too time-
eating to remedy manually. Using effective computers and algorithms to execute various
statistical techniques that analyze information in distinctive methods, customers can identify
patterns, developments, and relationships they could in any other case omit. They can then
practice these findings to expect what is possibly to take place inside the destiny and take
movement to influence commercial enterprise effects. Data mining is used in lots of areas of
commercial enterprise and studies, together with sales and advertising and marketing, product
improvement, healthcare, and education (Virtanen, 2021). When used efficiently, statistics
mining can come up with an advantage over competitors through making it feasible to examine
extra about clients, develop effective advertising strategies, increase sales, and decrease prices.
What are the advantages and disadvantages of data mining in crime rate prediction?
As per the viewpoint of Chauhan and Sehgal (2017), there are various advantages and
disadvantages of data mining in crime rate prediction. The advantages which can be gained
through data mining in crime rate prediction is that it helps in gathering reliable information, cost
effective solution as compared to other data prediction, detect crime, analyse enormous amount
of data quickly, predict the future crime and discover hidden patterns. These advantages help to

make informed decisions and also detect risks and fraud. Data mining helps in uncovering the
hidden facts and information from large database of criminal records for controlling, preventing
and investigating the crime for particular case. Crime data is useful for police department as it
can reduce their workload. The information gathered through data mining can also be used for
local crime pattern analysis and also provide insight view of well reported and well recorded
crime. There are several disadvantages of data mining in crime rate prediction which can
influence the performance of police department. It is important for police force to identify the
challenges faced by using data mining techniques in crime rate prediction. The disadvantage of
data mining tools are its costly process, need to conduct accurately, data can be misused,
complex and challenging to use and also it requires large database.
Predictive policing refers to the use of predictive analytics primarily based on mathematical
fashions, and different analytical strategies in law enforcement to become aware of potential
crook hobby. Predictive policing consequently makes use of pc structures to research massive
sets of records to assist decide where to install police or to pick out folks that are purportedly
more likely to commit or be a victim of against the law. Predictive policing has the potential to
make policing fairer (Xu and et.al., 2021). By promoting selection-making based on objective
proof, predictive policing should probably alleviate positive discrepancies within the
enforcement of the regulation. When the set of rules compiled the crime hot spot map within the
above-referred to LA have a look at, it did now not directly rely on prejudice. By contrast, the
traditional LAPD hot spot maps were produced via (inevitably prejudiced) people. As a end
result, algorithms is probably capable of help law enforcement officials to higher predict
dangers, determine the identification of offenders, and identify the vulnerabilities of a
community and its contributors. However, this capability can simplest be realised if the set of
rules is indeed freed from bias, which isn't always the case. Crime facts is useful for police
branch as it is able to lessen their workload. The statistics amassed through information mining
also can be used for local crime pattern analysis and additionally provide perception view of
properly reported and nicely recorded crime. There are several hazards of information mining in
crime fee prediction which can affect the performance of police branch. It is crucial for police
pressure to identify the challenges confronted through using information mining strategies in
crime price prediction. The disadvantage of records mining gear are its high priced manner, want
to behavior as it should be, information can be misused, complicated and hard to apply and also

it calls for large database. Predictive policing refers to using predictive analytics primarily based
on mathematical models, and distinct analytical strategies in regulation enforcement to emerge as
privy to capacity crook interest. Data mining facilitates in solving the crimes quicker and this
approach offers good results whilst implemented on crime dataset, the records acquired from the
data mining techniques can assist the police department. Produce crucial outcomes from crime
document datasets. The very step in study of crime is crime evaluation.
When it involves the use of records to predict crime warm spots, many years of
criminology studies show that crime reviews and different data amassed by using the police
frequently report law enforcement’s response to the reviews they receive and situations they
come upon, in preference to imparting an objective or complete record of all of the crimes that
occur. Put in any other case, the databases inform us where crime has been spotted by way of the
police in the past. But we recognise that in many nations the police devote disproportionate
assets concentrated on sure minority organizations. The end result is that racist practices get
baked into the statistics. Predictive policing then becomes a vicious circle. Crime records
gathered on the idea of a racist coverage will create racist predictions, leading to over-policing so
that the can hold to generate misleading records and racist predictions. Predictive policing
structures exacerbate this trend by making policing merely approximately the numeric discount
of the fees of detected, rather than actual, crime.
How data mining helps in prediction of crime rate in UK?
As per the viewpoint of Yerpude (2020), data mining helps in predicting the crime rate in
UK by increasing advent of computerized system. Through using data mining, crime data analyst
can also help law enforcement officers to solve the crimes in effective and efficient manner. By
implementing the concept of data mining, the police department can gain useful and unknown
information from unstructured data. Data mining is used for predicting the crime rate in UK by
using artificial intelligence methods due to which the crime data can be automatically entered
into database. Classification is one of the techniques of data mining that helps in predicting about
the values of data (Farsi and et. al., 2018). The crime is predicted through field research and
content analysis. In field research, police forces focus on observing characteristics of locations
whereas content analysis is used for examining the police report narratives. Link analysis is
known as data mining technique which is useful in the detection of valid and useful patterns. The
main framework of this analysis totally depends upon the fact of linking one activity with

another. Data mining is a manner to extract information out of normally big information units; in
other phrases it's far an technique to find out hidden relationships amongst statistics via using
artificial intelligence methods. By the usage of this technique, crime facts can be mechanically
entered into a database, in law enforcement companies.
Data mining techniques are used to operate on large amount of data to discover hidden
patterns and relationships helpful in decision making. Classification is a predictive data mining
technique, makes prediction about values of data using known results found from different data.
The five basic steps in the crime analysis process include the collection, categorization, analysis,
dissemination, and evaluation of information. The reports and forms for use in each step of
information-gathering and analysis are explained and illustrated. Crime forecasting refers to the
basic process of predicting crimes before they occur. Tools are needed to predict a crime before
it occurs. Currently, there are tools used by police to assist in specific tasks such as listening in
on a suspect's phone call or using a body cam to record some unusual illegal activity. Predicting
Crime and Other Uses of Neural Networks in Police Decision Making. Neural networks are a
machine learning method that excel in solving classification and forecasting problems. They
have also been shown to be a useful tool for working with big data oriented environments such
as law enforcement. Criminology is one of the maximum crucial fields for applying statistics
mining. Criminology is a process that aims to discover crime characteristics. Actually crime
analysis includes exploring and detecting crimes and their relationships with criminals. Data
mining allows to expand clever market selection, run accurate campaigns, make predictions, and
greater; With the assist of Data mining, we're in a position to research consumer behaviors and
their insights. This effects in exceptional achievement and statistics-driven commercial
corporation. Use of records mining techniques can produce vital consequences from crime report
datasets. The very step in have a take a look at of crime is crime analysis. Crime assessment is
exploring, inter pertaining to and detecting courting the various numerous crimes and traits of the
crime. This analysis permits in making equipped statistics, queries and maps on demand. It
additionally permits to peer if a criminal offense in a certain recognized sample or a brand new
pattern essential.
Data mining is a way to extract expertise out of usually massive facts sets; in different
words it's miles an technique to find out hidden relationships among facts with the aid of the use
of synthetic intelligence methods. By the use of this method, crime facts may be automatically