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Top 100 Big Data Research Topics For Students

big data research topics

Selecting the right big data research topics is the first and most important step in the process of writing academic papers or essays. Big data is becoming a popular phenomenon among scholars and practitioners. The multidisciplinary background of big data research encompasses a wide spectrum that covers scientific publications in different study areas.

Nevertheless, some students have difficulties choosing big data topics for their computer science thesis or research paper. That’s because finding information to write about some topics is not easy. To solve this problem, we list the top 100 topics in data science that learners can choose from.

Trendy Big Data Research Topics

Students that want to focus on emerging issues when writing academic papers and essays should choose trendy data science topics. Big data covers the initiatives and technologies that tackle massive and diverse data when it comes to addressing traditional skills, technologies, and infrastructure efficiently. Here are some of the latest data topics to consider when writing a research paper or essay.

These are great data research topics that learners at different study levels should consider when asked to write academic papers or essays. However, extensive research is required to come up with great write-ups on these topics.

Data Mining Research Topics for Students

Data mining refers to the extraction of useful information from raw data. It’s a technique that companies apply to accomplish tasks like prediction analysis, generation of the association rule, and clustering. Data mining topics can explain this technique or address issues that are associated with it. Here are some of the best data mining project topics that learners can consider.

Most data mining current research topics focus on finding or establishing patterns. Students can even find some of the best data mining case study topics in this category. Nevertheless, every idea requires detailed and extensive research to come up with facts that make a great paper or essay.

Big Data Analysis Topics

The moderns IT industry depends on data analytics as its lifeline. Big data is one of the techniques and technologies that are used to analyze vast data volumes. The industry is using data analytics as a strategy for gaining insights into system performance and customer behavior. Here are some of the best data analytics research topics that students can consider when writing academic papers.

Writing about data analytics topics requires background knowledge of the issues being discussed. That’s because the analysis entails harnessing data and extracting its value.

Data Management Project Topics

This category has some of the best data science research topics. The enormous amount of data that modern organizations have to deal with every day is not easy to handle. As such, its effective management is required to ensure its effective use. Here are some of the best topics that students can write about in this aspect.

This category also has some of the best big data seminar topics. That’s because some of the ideas featured in this section are about issues that affect almost every organization.

Resent Data Security Topics for Research

Big data that comes from different computers and devices require security. That’s because such data is vulnerable to different cyber threats. Some of the best research topics in this category include the following.

Any topic in this category can be used to write a brilliant paper or essay that will earn the learner the top grade. However, time and efforts are required to work on these ideas.

Whether students opt to write about data visualization topics or data structure research topics, the most important thing is to choose ideas they like and find interesting. What’s more, learners should pick topics they can find adequate information for online. That way, they will find the research and writing process enjoyable. They can also buy dissertations or any other academic papers that will impress educators to award them the top grades.

Geology Research Topics

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Thesis Topics in Data Mining

Data mining has been increasingly gathering attention in recent years. That is why there are plenty of relevant thesis topics in data mining. Consequently, in order to choose a good topic, one has to consider several aspects regarding the area, techniques, and purpose of the study, starting with the choice between theory and practice, or, perhaps, concentrate on both. What is the most important is that the topic should appeal to the student as there are so many possible thesis topics in data mining that he or she is likely to get confused while making a proper choice of the most relevant one.

“So what should I do my thesis about?” Look what you can explore in your thesis.

Data Mining and User Privacy

Privacy protection has been a concern for public policy makers for decades. The development of more complex methods of collecting and analyzing personal information has made privacy a major issue for public and government domains. Specifically, the rise of data mining has put the issue of privacy in a new light. Data mining refers to the process of discovering patterns and knowledge from massive amounts of data. The process lies in employing different prospectives to data analysis and generating useful information. It has been applied to a variety of domains, such as Web research, scientific discovery, business intelligence, and homeland security.

Although the information that data mining can discover may be valuable and have a variety of applications and even help to fight terrorism, it poses a serious threat to privacy. Such technology can be easily abused especially taking into consideration the fact that many customers are not aware that their purchases and the publicly shared information are mined. For instance, when one fills out an application for a loan, the information the person submits will most likely be put in a database. Moreover, the information will probably not stay in one place; it can be sold or, either intentionally or not, put on the Internet and become available to everyone. Furthermore, the violation of individual’s privacy can occur due to other factors, for instance, data mining tools may access private information without authorization, discover undesired information, or use the data for purposes that differ from the one for which it was collected.

However, there might be a resolution for the issue that lies in the data mining subdivision called privacy preserving data mining. Its objective is to protect sensitive information from disclosure and, at the same time, preserve its utility. The technology prevents sensitive data, such as telephone and ID card numbers, from being directly used for mining as well as excludes the results the disclosure of which would lead to a violation of privacy. Another approach to eliminating privacy concerns is to mine data from distributed sources. In this case, there will be no need to disclose the data that will eliminate the massive databases, which are the main reason behind the concerns. According to this approach, the individual data is split among different sites. As a result, it will require compromising several databases in order to obtain enough information about an individual.

All in all, even though data mining can be a useful tool for detecting fraud, assessing product retailing, and identifying terrorist activities, it poses a threat of invading individual privacy. There are, however, several ways to minimize this disadvantage, such as the use of privacy preserving data mining and mining data from distributed sources.


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Trending Data Mining Thesis Topics

            Data mining seems to be the act of analyzing large amounts of data in order to uncover business insights that can assist firms in fixing issues, reducing risks, and embracing new possibilities . This article provides a complete picture on data mining thesis topics where you can get all information regarding data mining research

How to Implement Data Mining Thesis Topics

How does data mining work?

  The techniques and actions listed above are repeated until the best outcomes are achieved. Our engineers and developers have extensive knowledge of the tools, techniques, and approaches used in the processes described above. We guarantee that we will provide the best research advice w.r.t to data mining thesis topics and complete your project on schedule. What are the important data mining tasks?

Data Mining Tasks 

You can look at our website for a more in-depth look at all of these operations. We supply you with the needed data, as well as any additional data you may need for your data mining thesis topics . We supply non-plagiarized data mining thesis assistance in any fresh idea of your choice. Let us now discuss the stages in data mining that are to be included in your thesis topics

How to work on a data mining thesis topic? 

 The following are the important stages or phases in developing data mining thesis topics.

Usually, our experts help in writing codes and implementing them successfully without hassles . By consistently following the above steps you can develop one of the best data mining thesis topics of recent days. Furthermore, technically it is important for you to have a better idea of all the tasks and techniques involved in data mining about which we have discussed below

If you are looking forward to selecting the best tool for your data mining project then evaluating its consistency and efficiency stands first. For this, you need to gain enough technical data from real-time executed projects for which you can directly contact us. Since we have delivered an ample number of data mining thesis topics successfully we can help you in finding better solutions to all your research issues. What are the points to be remembered about the data mining strategy?

All such pros and cons of various data mining aspects are discussed on our website. We will provide you with high-quality research assistance and thesis writing assistance . You may see proof of our skill and the unique approach that we generated in the field by looking at the samples of the thesis that we produced on our website. We also offer an internal review to help you feel more confident. Let us now discuss the recent data mining methodologies

Current methods in Data Mining

Our technical specialists and technicians usually give adequate accurate data, a thorough and detailed explanation, and technical notes for all of these processes and algorithms. As a result, you can get all of your questions answered in one spot. Our technical team is also well-versed in current trends, allowing us to provide realistic explanations for all new developments. We will now talk about the latest data mining trends

Latest Trending Data Mining Thesis Topics

These are the recent trends in data mining. We insist that you choose one of the topics that interest you the most. Having an appropriate content structure or template is essential while writing a thesis . We design the plan in a chronological order relevant to the study assessment with this in mind. The incorporation of citations is one of the most important aspects of the thesis. We focus not only on authoring but also on citing essential sources in the text. Students frequently struggle to deal with appropriate proposals when commencing their thesis. We have years of experience in providing the greatest study and data mining thesis writing services to the scientific community, which are promptly and widely acknowledged. We will now talk about future research directions of research in various data mining thesis topics

Future Research Directions of Data Mining

The Internet of Things as well as wearable electronics, for instance, has transformed devices to be connected into data-generating engines which provide limitless perspectives into people and organizations if firms can gather, store, and analyze the data quickly enough. What are the aspects to be remembered for choosing the best  data mining thesis topics?

Our engineers and experts can provide you with any type of research assistance on any of these data mining development tools . We satisfy the criteria of your universities by ensuring several revisions, appropriate formatting and editing of your thesis, comprehensive grammar check, and so on . As a result, you can contact us with confidence for complete assistance with your data mining thesis. What are the important data mining thesis topics?

Trending Data Mining Research Thesis Topics

Research Topics in Data Mining

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1. IvyPanda . "79 Data Mining Essay Topic Ideas & Examples." January 21, 2023.


IvyPanda . "79 Data Mining Essay Topic Ideas & Examples." January 21, 2023.

IvyPanda . 2023. "79 Data Mining Essay Topic Ideas & Examples." January 21, 2023.

IvyPanda . (2023) '79 Data Mining Essay Topic Ideas & Examples'. 21 January.

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Master thesis topics [closed]

I am looking for a thesis to complete my master, I am interested in Predictive Analytics in marketing, HR, management or financial subject, using Data Mining Application.

I have found a very interesting subject: "Predicting customer churn using decision tree" or either "Predicting employee turnover using decision tree", I looked around very hard but unfortunately couldn't find any relevant dataset to download ( Telecommunication Customer churn Dataset ).

I would like to work on a similar subject using "Decision Tree Technique".

Please suggest some topics or project that would make for a good masters thesis subject.

  • data-mining
  • predictive-modeling
  • decision-trees

Community's user avatar

2 Answers 2

This is the approach I took:

  • Find journals related to your field of studies
  • Skim through the proceedings, see if there are titles that catch your interest
  • Read the papers (carefully or globally) that seemed interesting
  • Carefully consider the approaches and whatever future suggestions they present in their papers
  • Think critically: What would you change? What do you want to find out? Don't limit yourself to data but rather orient from the perspective of research. Solutions for data might only become apparent when you know exactly what you want to examine.

I think this has advantages because these papers outline details regarding data as well -- perhaps you can use the same.

Present some papers and your idea to your prospective supervisor and he/she will make some suggestions. Researchers generally have a lot of knowledge about the possibilities and might even be curious about some things themselves.

Good luck! And enjoy.

lennyklb's user avatar

First, talk to your thesis advisor before committing to a project. They know better than I do.

Secondly, just analyzing a new dataset using standard techniques doesn't make for a good masters thesis. Your project is expected to use some sort of novel approach.

With that said, I'd suggest that you start by reading up on existing decision tree techniques, learning why they work and what their flaws are, and try to find ways to overcome the flaws. Then, once you have your improvement, it should be relatively easy to find a dataset to apply it to.

Timothy Nodine's user avatar

Not the answer you're looking for? Browse other questions tagged data-mining predictive-modeling bigdata decision-trees research or ask your own question .

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Data Mining Dissertation Topics

           The term “data mining” refers to an intelligent data lookup capacity that uses statistics-based algorithms and methodologies to find trends, patterns, links, and correlations within the collected data and records. Audio, Pictorial, Video, textual, online, and social media-based mining are only a few examples of data mining. This article will provide you with a complete overview of various recent data mining dissertation topics . Let us first start with the definition of data mining processes.  

Trending Data Mining Dissertation Topics for Research Scholars

What is the data mining process?

  • The practice of evaluating a huge batch containing data to find different patterns is known as data mining.
  • Companies can utilize data mining for a variety of purposes, including knowing as to what consumers are engaged in or would like to buy, as well as detection of fraudulent activities and malware scanning.

Hence data mining plays a very significant role in both commercial and personal life aspects of the modern world. We have been working on data mining dissertation topics and project ideas for more than 15 years as a result of which we have gained huge expertise and have acquired vast knowledge, skills, and experience in the field. So we can guide you in all the existing and normal data mining methods and techniques. Let us now talk about the data mining techniques below  

Data mining techniques 

  • Neural networks
  • Rule induction
  • Nearest neighbor classification
  • Decision tree
  • Descriptive techniques – sequential analysis, association, and clustering

Complete explanation and description on all these techniques and methods are available at our website on data mining dissertation topics . By understanding the importance of data mining, we have successfully worked out several advanced projects and implementations in real-time . Check out our website for all details about our successful projects in data mining. Let us now see about the data mining approaches below  

Approaches in data mining

This is the basic classification of the various data mining approaches that are in use today. With the support of the best engineers and world-class certified experts in data mining , we are here to provide you with a massive amount of reliable and authentic research data along with complete support in interpretation, analysis, and understanding them . Get in touch with us at any time for complete support for your data mining dissertation . We assure to give you full support and ultimate guidance on any data mining dissertation topics.  We will now talk about the major issues in data mining

Major issues in data mining

We have handled all these issues efficiently and have devised successful methods to overcome them. Get in touch with us to know more about the potential data mining solutions and advanced techniques used in overcoming the issues of data mining . What are the top data mining topics?  

Top 5 Data Mining Dissertation Topics

In recent years, there has been a spike in demand for data mining and associated sectors. You could stay up with the current tendencies and advancements using the data mining projects and subjects listed above. So, maintain your curiosity stimulated and the knowledge updated.

We have successfully delivered all these project topics and dissertation works . Our technical team and writers are highly qualified and are intended solely to establish successful projects into reality. So you can readily contact our customer support facility anytime regarding doubts and queries related to data mining . Let us now see about data mining implementation tools below

Data Mining Tools

The tips and advice in using these tools of data mining are explained in detail on our website. Also, we are here to help you in handling these data mining tools efficiently with proper demonstrations and explanations. Our engineers have great skills in working with these data mining tools. So reach out to us for any support related to data mining. What are the recent trends in data mining?  

Latest trends in data mining

At present we are offering complete project support and dissertation writing guidance along with assignments, paper publication, proposal, thesis, and many more with proper grammatical checks, full review, and approval. Therefore we are here to help you in all aspects of your data mining research . What are the Datasets available for data mining?  

Datasets for Data Mining Projects

Apart from these relevant datasets, there are also many other datasets including CIDDS, DAPARA, CICIDS2017, ADFA – IDS, TUIDS, ISCXIDS2012, AWID, and NSL – KDD . Complete information on all these datasets and tips for handling them efficiently will be shared with you as you avail of our services on data mining dissertation topics . Feel free to interact with our experts regarding any doubts in your data mining research. We ensure to solve all your doubts instantly.

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16 Data Mining Projects Ideas & Topics For Beginners [2023]

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Rohit Sharma is the Program Director for the UpGrad-IIIT Bangalore, PG Diploma Data Analytics Program.

Table of Contents

Data Mining Projects

Today, data mining has become strategically important to organizations across industries. It not only helps in predicting outcomes and trends but also in removing bottlenecks and improving existing processes. Data mining research topics 2020 was already in the search bar of millions of users 2 years ago . It looks like this trend is about to continue in 2023 and beyond. So, if you are a beginner, the best thing you can do is work on some real-time data mining projects.

 If you are just getting started in data science, making sense of advanced data mining techniques can seem daunting. Along with the plethora of data mining research topics available online , we have compiled some useful data mining project topics to support you in your learning journey.

We, here at upGrad, believe in a practical approach as theoretical knowledge alone won’t be of help in a real-time work environment if you do not work on data mining projects yourself . In this article, we will be exploring some fun and exciting data mining projects and data mining research topics which beginners can work on to put their data mining knowledge to test. In this post, you will learn about top 16 data mining projects for beginners.

In this article, you will find 42 top python project ideas  for beginners to get hands-on experience on Python

But first, let’s address the more important and frequently question that must be lurking in your mind: why to build data mining projects ?

But before we begin, let us look at an example to decode what data mining is all about. Suppose you have a data set containing login logs of a web application. It can include things like the username, login timestamp, activities performed, time spent on the site before logging out, etc.

Our learners also read : Python online course free !

Such unstructured data in itself would not serve any purpose unless it is organized systematically and analyzed to extract relevant information for the business. By applying the different techniques of data mining, you can discover user habits, preferences, peak usage timings, etc. These insights can further increase the software system’s efficiency and boost its user-friendliness. Learn more about data mining with our data science programs.

data mining projects

In today’s digital era, the computing processes of collecting, cleaning, analyzing, and interpreting data make up an integral part of business strategies. So, data scientists are required to have adequate knowledge of methods like pattern tracking, classification, cluster analysis, prediction, neural networks, etc. The more you experiment with different  data mining projects , the more knowledge you gain.

Data Mining Project Ideas & Topics for Beginners

This list of  data mining projects for students is suited for beginners, and those just starting out with Data Science in general. These  data mining projects will get you going with all the practicalities you need to succeed in your career.

Further, if you’re looking for data mining project for final year, this list should get you going as this list also contains data mining projects for students . So, without further ado, let’s jump straight into some data mining projects that will strengthen your base and allow you to climb up the ladder.

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1. iBCM: interesting Behavioral Constraint Miner

One of the best ideas to start experimenting you hands-on  data mining projects for students is working on iBCM. A sequence classification problem deals with the prediction of sequential patterns in data sets. It discovers the underlying order in the database based on specific labels. In doing so, it applies the simple mathematical tool of partial orders. However, you would require a better representation to achieve more accurate, concise, and scalable classification. And a sequence classification technique with a behavioral constraint template can address this need.

The interesting Behavioral Constraint Miner (iBCM) project can express a variety of patterns over a sequence, such as simple occurrence, looping, and position-based behavior. It can also mine negative information, i.e., the absence of a particular behavior. So, the iBCM approach goes much beyond the typical sequence mining representations and is a perfect starting point for those looking for data mining projects for students.

2. GERF: Group Event Recommendation Framework

This is one of the  simple data mining projects yet an exciting one. It is an intelligent solution for recommending social events, such as exhibitions, book launches, concerts, etc. A majority of the research focuses on suggesting upcoming attractions to individuals. So, a Group Event Recommendation Framework (GERF) was developed to propose events to a group of users.

This model uses a learning-to-rank algorithm to extract group preferences and can incorporate additional contextual influences with ease, accuracy, and time-efficiency.

Learning to rank, also known as machine-learned ranking (MLR), is the process of building ranking models for systems needing information retrieval using machine learning techniques such as supervised learning, semi-supervised learning, and reinforcement learning.

The objects used for training are organized into lists, with the relative order between the lists being partially described. In most cases, a number or ordinal score is assigned to each item, or a binary judgment (such as “relevant” for true values(binary 1) or “not relevant” for false values(binary 0)) is made.

The objective of the ranking model is to apply the same logic used to rank the training data to the rating of fresh, unknown lists.

Also, it can be conveniently applied to other group recommendation scenarios like location-based travel services. 

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3. Efficient similarity search for dynamic data streams

Online applications use similarity search systems for tasks like pattern recognition, recommendations, plagiarism detection, etc. Typically, the algorithm answers nearest-neighbor queries with the Location-Sensitive Hashing or LSH approach, a min-hashing related method. It can be implemented in several computational models with large data sets, including MapReduce architecture and streaming. Mentioning  data mining projects can help your resume look much more interesting than others.

Dynamic data streams, however, require scalable LSH-based filtering and design. To this end, the efficient similarity search project outperforms previous algorithms. Here are some of its main features:

4. Frequent pattern mining on uncertain graphs

Application domains like bioinformatics, social networks, and privacy enforcement often encounter uncertainty due to the presence of interrelated, real-life data archives. This uncertainty permeates the graph data as well.

This problem calls for innovative data mining projects that can catch the transitive interactions between graph nodes. This beginner-level data mining projects will help build a strong foundation for fundamental programming concepts. One such technique is the frequent subgraph and pattern mining on a single uncertain graph. The solution is presented in the following format:

5. Cleaning data with forbidden itemsets or FBIs

Data cleaning methods typically involve taking away data errors and systematically fixing the issue by specifying constraints (illegal values, domain restrictions, logical rules, etc.)  

In the real-life big data universe, we are inundated with dirty data that comes without any known constraints. In such a scenario, the algorithm automatically discovers constraints on the dirty data and further uses them to identify and repair errors. But when this discovery algorithm runs on the repaired data again, it introduces new constraint violations, rendering the data erroneous. This is one of the excellent data mining projects for beginners.

Hence, a repairing method based on forbidden itemsets (FBIs) was devised to record unlikely co-occurrences of values and detect errors with more precision. And empirical evaluations establish the credibility and reliability of this mechanism. 

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6. protecting user data in profile-matching social networks.

This is one of the convenient data mining projects that has a lot of use in the future. Consider the user profile database maintained by the providers of social networking services, such as online dating sites. The querying users specify certain criteria based on which their profiles are matched with that of other users. This process has to be secure enough to protect against any kind of data breaches. There are some solutions in the market today that use homomorphic encryption and multiple servers for matching user profiles to preserve user privacy. 

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7. privrank for social media.

Social media sites mine their users’ preferences from their online activities to offer personalized recommendations. However, user activity data contains information which can be used to infer private details about an individual (for example, gender, age, etc.) And any leak or release of such user-specified data can increase the risk of interference attacks. 

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8. Practical PEKs scheme over encrypted email in cloud server

In the light of current high-profile public events related to email leaks, the security of such sensitive messages has emerged as a primary concern for users worldwide. To that end, the Public Encryption with Keyword Search (PEKS) technology offers a viable solution. This is one of the useful data mining projects in which this combines security protection with efficient search operability functions. 

When searching over a sizable encrypted email database in a cloud server, we would want the email receivers to perform quick multi-keyword and boolean searches without revealing additional information to the server.

Read: Data Mining Real World Applications

9. Sentimental analysis and opinion mining for mobile networks

This project concerns post-publishing applications where a registered user can share text posts or images and also leave comments on posts. Under the prevailing system, users have to go through all the comments manually to filter out verified comments, positive comments, negative remarks, and so on.

With the sentiment analysis and opinion mining system, users can check the status of their post without dedicating much time and effort. It provides an opinion on the comments made on a post and also gives the option to view a graph. 

10. Mining the k most frequent negative patterns via learning

In behavior informatics, the negative sequential patterns (NSPs) can be more revealing than the positive sequential patterns (PSPs) . For instance, in a disease or illness-related study, data on missing a medical treatment can be more useful than data on attending a medical procedure. But to the present day, NSP mining is still at a nascent stage. And the ‘Topk-NSP+’ algorithm presents a reliable solution for overcoming the obstacles in the current mining landscape. This is one of the trending data mining and this is how the project proposes the algorithm:

Also try:  Machine Learning Project Ideas for Beginners

11. Automated personality classification project

The automatic system analyzes the characteristics and behaviors of participants. And after observing the past patterns of data classification, it predicts a personality type and stores its own patterns in a dataset. This project idea can be summarized as follows:

Such models are commonplace in career guidance services where a student’s personality is matched with suitable career paths. This can be an interesting and useful data mining projects.

12. Social-Aware social influence modeling

This is one of the most popular data mining mini projects. This project deals with big social data and leverages deep learning for sequential modeling of user interests. The stepwise process is described below:

Experimental results reveal that the structure of this proposed solution enables higher prediction accuracy as compared to other baseline methods.

This is one of the data mining mini projects that will definitely help you get some real-world exposure.

13. Predicting consumption patterns with a mixture approach

Individuals consume a large selection of items in the digital world today. For example, while making purchases online, listening to music, using online navigation, or exploring virtual environments. Applications in these contexts employ predictive modeling techniques to recommend new items to users. However, in many situations, we want to know the additional details of previously-consumed items and past user behavior. And this is where the baseline approach of matrix factorization-based prediction falls short. This is one of the creative data mining projects. 

A mixture model with repeated and novel events offers a suitable alternative for such problems. It aims to deliver accurate consumption predictions by balancing individual preferences in terms of exploration and exploitation. Also, it is one of those data mining project topics that include an experimental analysis using real-world datasets. The study’s results show that the new approach works efficiently across different settings, from social media and music listening to location-based data. 

14. GMC: Graph-based Multi-view Clustering 

The existing clustering methods for multi-view data require an extra step to produce the final cluster as they do not pay much attention to the weights of different views. Moreover, they function on fixed graph similarity matrices of all views. And this is the perfect idea for your next data mining project as this can also be considered as a graph mining projects .

A novel Graph-based Multi-view Clustering (GMC) can tackle this issue and deliver better results than the previous alternatives. It is a fusion technique that weights data graph matrices for all views and derives a unified matrix, directly generating the final clusters. Other features of the graph mining projects include:

15. ITS: Intelligent Transportation System

A multi-purpose traffic solution generally aims to ensure the following aspects:

Consider a project that uses the above system to optimize the process of bus scheduling in a city. ITS is one of the interesting data mining projects for beginners. You can take the past three years’ data from a renowned bus service company, and apply uni-variate multi-linear regression to conduct passengers’ forecasts.

Further, you can calculate the minimum number of buses required for optimization in a Generic Algorithm. Finally, you validate your results using statistical techniques like mean absolute percentage error (MAPE) and mean absolute deviation (MAD). Mean Absolute Percentage Error(MAPE): The accuracy of a forecasting system may be quantified by calculating the mean absolute percentage error (MAPE). Measured as a percentage, it is derived by taking the sum of the absolute values of the errors across all time periods and dividing by the real values to provide a reading on how close the estimate is to the true value.

The most popular way to quantify forecast errors is via the use of the mean absolute percentage error (MAPE), perhaps because the variable’s units are already in percentage form. A lack of extremes in the data is necessary for optimal performance (and no zeros). In regression analysis and model assessment, it is frequently used as a loss function.

Mean Absolute Deviation(MAD): It measures how far each data point is from the dataset’s mean value. It helps us get a sense of the data’s overall dispersion. To find out the MAD for a data set, we must first calculate the mean and then the distance of each data point from the mean using MPD(Mean positive distances) which would yield the absolute deviation.

This absolute deviation is the measure of this gap between the mean and each data point. Now, we take the total of all these deviations, add it and then divide it by the total number of data points in the data set.

Also read: Data Science Project Ideas

16. TourSense for city tourism

City-scale transport data about buses, subways, etc. could also be used for tourist identification and preference analytics. But relying on traditional data sources, such as surveys and social media, can result in inadequate coverage and information delay.

The TourSense project demonstrates how to override such shortcomings and provide more valuable insights. This tool would be useful for a wide range of stakeholders, from transport operators and tour agencies to tourists themselves. This is one of the excellent data mining projects for beginners. Here are the main steps involved in its design: 

Data Mining Projects: Conclusion

In this article, we have covered 16 data mining projects . If you wish to improve your data mining skills, you need to get your hands on these data mining projects.

Data mining and correlated fields have experienced a surge in hiring demand in the last few years as data mining research topics 2020 was already in the search bar of millions of users 2 years ago and is still there . With the above data mining project topics, you can keep up with the market trends and developments. So, stay curious and keep updating your knowledge!

If you are curious to learn about data science, check out IIIT-B & upGrad’s Executive PG Program in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

What do you mean by data mining?

As the name suggests, data mining refers to the process of mining or extraction of patterns from large data sets. The methods it involves include the combined knowledge of machine learning, statistics, and database systems. Before applying data mining techniques, you need to assemble a large dataset that must be large enough to contain patterns to be mined. There are 6 prominent steps that are involved in the data mining process. These steps are anomaly detection, association rule learning, clustering, classification, regression, and summarization.

Discuss the significance of classification in data mining.

Classification in data mining allows enterprises to arrange large sets of data according to the target categories. Once ordered in this manner, the enterprises could see the data clearly and analyze the risks and profits easily which in turn helps the businesses to grow. Classification can also be understood as a way to generalize known structures to apply to new data. The analysis is based on several patterns that are found in the data. These patterns help to sort the data into different groups.

Why should I build projects in data mining?

Projects are all about experimenting and testing your skills. They let you use all of your creativity and develop a useful product out of it. Building data mining projects will not only give you hands-on experience but will also enhance your knowledge pool. You can add these amazing projects to your resume to showcase your skills to potential employers. These projects will help you to implement your theoretical knowledge into action and gain practical benefits from it.

data mining thesis topics

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    I am looking for a thesis to complete my master, I am interested in Predictive Analytics in marketing, HR, management or financial subject, using Data Mining Application. I have found a very interesting subject: "Predicting customer churn using decision tree" or either "Predicting employee turnover using decision tree", I looked around very hard but unfortunately couldn't find any relevant dataset to download ( Telecommunication Customer churn Dataset ).

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    This can be an interesting and useful data mining projects. 12. Social-Aware social influence modeling This is one of the most popular data mining mini projects. This project deals with big social data and leverages deep learning for sequential modeling of user interests. The stepwise process is described below: