Why Data Mining Projects ?

Data mining is a cornerstone of analytics, helping you develop the models that can uncover connections within millions or billions of records. Data mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis. Data mining tools allow enterprises to predict future trends. Data mining is the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. Using a broad range of techniques, you can use this information to increase revenues, cut costs, improve customer relationships, reduce risks and more. Here is the list of important areas where data mining is widely used : Future Healthcare , Market Basket Analysis , Education , Manufacturing Engineering , Customer Relationship Management , Fraud Detection , Intrusion Detection , Customer Segmentation , Financial Banking , Corporate Surveillance , Research Analysis , Criminal Investigation and Bio Informatics.

Latest 2023 Data Mining Projects Titles

Project Code	Project Title
DM2019001	Achieving Data Truthfulness and Privacy Preservation in Data Markets
DM2019002	Comments Mining With TF-IDF: The Inherent Bias and Its Removal
DM2019003	l-Injection: Toward Effective Collaborative Filtering Using Uninteresting Items
DM2019004	Order-Sensitive Imputation for Clustered Missing Values
DM2019005	Predicting Consumption Patterns with Repeated and Novel Events

Latest 2018 Data Mining Projects Titles

Project Code	Project Title
DM2018001	Exploring Hierarchical Structures for Recommender Systems
DM2018002	Longest Increasing Subsequence Computation over Streaming Sequences
DM2018003	Multi-instance Learning with Discriminative Bag Mapping
DM2018004	Multi-Label Learning with Global and Local Label Correlation
DM2018005	Profit Maximization for Viral Marketing in Online Social Networks: Algorithms and Analysis
DM2018006	Range Queries on Multi-Attribute Trajectories
DM2018007	RNN-DBSCAN: A Density-based Clustering Algorithm using Reverse Nearest Neighbor Density Estimates
DM2018008	Scalable Content-Aware Collaborative Filtering for Location Recommendation
DM2018009	Space Filling Approach for Distributed Processing of Top-k Dominating Queries
DM2018010	Structure Based User Identification across Social Networks
DM2018011	Supervised Topic Modeling using Hierarchical Dirichlet Process-based Inverse Regression: Experiments on E-Commerce Applications
DM2018012	Heterogeneous Metric Learning of Categorical Data with Hierarchical Couplings
DM2018013	A Comprehensive Study on Social Network Mental Disorders Detection via Online Social Media Mining
DM2018014	Heterogeneous Metric Learning of Categorical Data with Hierarchical Couplings
DM2018015	Leveraging Conceptualization for Short-Text Embedding
DM2018016	Multi-View Missing Data Completion
DM2018017	Road Traffic Speed Prediction: A Probabilistic Model Fusing Multi-Source Data
DM2018018	Sampling and Reconstruction Using Bloom Filters
DM2018019	A Deep Learning-Based Data Minimization Algorithm for Fast and Secure Transfer of Big Genomic Datasets
DM2018020	A Fast Parallel Community Discovery Model on Complex Networks Through Approximate Optimization
DM2018021	A Survey of Location Prediction on Twitter
DM2018022	A Two-Phase Algorithm for Differentially Private Frequent Subgraph Mining
DM2018023	AMDO: an Over-Sampling Technique for Multi-Class Imbalanced Problems
DM2018024	Capturing the Spatiotemporal Evolution in Road Traffic Networks
DM2018025	CRAFTER: a Tree-ensemble Clustering Algorithm for Static Datasets with Mixed Attributes and High Dimensionality
DM2018026	Health Monitoring on Social Media over Time
DM2018027	Link Weight Prediction Using Supervised Learning Methods and Its Application to Yelp Layered Network
DM2018028	Making a Small World Smaller: Path Optimization in Networks
DM2018029	On Generalizing Collective Spatial Keyword Queries
DM2018030	On Power Law Growth of Social Networks
DM2018031	Privacy Characterization and Quantification in Data Publishing
DM2018032	Privacy Enhanced Matrix Factorization for Recommendation with Local Differential Privacy
DM2018033	Querying a Collection of Continuous FunctionsUnsupervised Coupled Metric Similarity for Non-IID Categorical Data

Recent 2017 Data Mining Projects Titles

Project Code	Project Title
DM2017001	An Efficient Indexing Method for Skyline Computations with Partially Ordered Domains
DM2017002	Bag-of-Discriminative-Words (BoDW) Representation via Topic Modeling
DM2017003	Continuous Top-k Monitoring on Document Streams
DM2017004	Dynamic Facet Ordering for Faceted Product Search Engines
DM2017005	Efficient Processing of Skyline Queries Using MapReduce
DM2017006	Spectral Ensemble Clustering via Weighted K-means: Theoretical and Practical Evidence
DM2017007	A Scalable Data Chunk Similarity based Compression Approach for Efficient Big Sensing Data Processing on Cloud
DM2017008	A Unified Framework for Metric Transfer Learning
DM2017009	Analyzing Sentiments in One Go: A Supervised Joint Topic Modeling Approach
DM2017010	Data-driven Answer Selection in Community QA Systems
DM2017011	Efficient Top-k Dominating Computation on Massive Data
DM2017012	Keyword Search over Distributed Graphs with Compressed Signature
DM2017013	Modeling and Learning Continuous Word Embedding with Metadata for Question Retrieval
DM2017014	Online Multi-Task Learning Framework for Ensemble Forecasting
DM2017015	RAPARE A Generic Strategy for Cold-Start Rating Prediction Problem
DM2017016	Search Rank Fraud and Malware Detection in Google Play
DM2017017	User Vitality Ranking and Prediction in Social Networking Services a Dynamic Network Perspective
DM2017018	Bayesian Nonparametric Relational Topic Model through Dependent Gamma Processes
DM2017019	Collaboratively Training Sentiment Classifiers for Multiple Domains
DM2017020	Crowdsourced Coverage as a Service Two-Level Composition of Sensor Cloud Service
DM2017021	Discovering Newsworthy Themes From Sequenced Data A Step Towards Computational Journalism
DM2017022	Energy-efficient Query Processing in Web Search Engines
DM2017023	Engagement dynamics and sensitivity analysis of YouTube video
DM2017024	Enhancing Binary Classification by Modeling Uncertain Boundary in Three-Way Decisions
DM2017025	Human-Powered Data Cleaning for Probabilistic Reachability Queries on Uncertain Graphs
DM2017026	Local Suppression and Splitting Techniques for Privacy Preserving Publication of Trajectories
DM2017027	On Spectral Analysis of Signed and Dispute Graphs Application to Community Structure
DM2017028	Online Transfer Learning with Multiple Homogeneous or Heterogeneous Sources
DM2017029	Personal Web Revisitation by Context and Content Keywords with Relevance Feedback
DM2017030	Profiling Entities over Time in the Presence of Unreliable Sources
DM2017031	Query Expansion Folksonomy Data
DM2017032	Sparse Poisson Latent Block Model for Document Clustering