Data mining is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers and develop more effective marketing strategies as well as increase sales and decrease costs.

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IEEE Data-mining Projects 2019-20

S.No
Code
Title
Category
1
LMTDM01
Clustering-Based Collaborative Filtering Using an Incentivized/Penalized User Model
Data Mining-2019-2020
Abstract   
2
LMTDM02
A Hierarchical Attention Model for Social Contextual Image Recommendation
Data Mining--2019-2020
Abstract      
3
LMTDM03
Mining Users Trust From E-Commerce Reviews Based on Sentiment Similarity Analysis
Data Mining--2019-2020
Abstract      
4
LMTDM04
Old and Young Usersí White Space Preferences for Online News Web Pages
Data Mining--2019-2020
Abstract      
5
LMTDM05
Analysis and Accurate Prediction of Userís Response Behavior in Incentive-Based Demand Response
Data Mining--2019-2020
Abstract   
6
LMTDM06
DCCR: Deep Collaborative Conjunctive Recommender for Rating Prediction
Data Mining--2019-2020
Abstract   
7
LMTDM07
Network Representation Learning Enhanced Recommendation Algorithm
Data Mining--2019-2020
Abstract   
8
LMTDM08
Trust Relationship Prediction in Alibaba E-Commerce Platform
Data Mining--2019-2020
Abstract   
9
LMTDM09
Composition Context-Based Web Services Similarity Measure
Data Mining--2019-2020
Abstract   
10
LMTDM10
NASM: Nonlinearly Attentive Similarity Model for Recommendation System via Locally Attentive Embedding
Data Mining--2019-2020
Abstract   
11
LMTDM11
A Novel Load Image Profile-Based Electricity Load Clustering Methodology
Data Mining--2019-2020
Abstract   
12
LMTDM12
An Efficient Method for High Quality and Cohesive Topical Phrase Mining
Data Mining--2019-2020
Abstract   
13
LMTDM13
Privacy-Preserving Social Media Data Publishing for Personalized Ranking-Based Recommendation
Data Mining--2019-2020
Abstract   
14
LMTDM14
Secure and Efficient Skyline Queries on Encrypted Data
Data Mining--2019-2020
Abstract   
15
LMTDM15
A Hybrid E-learning Recommendation Approach Based on Learnersí Influence Propagation
Data Mining--2019-2020
Abstract   
16
LMTDM16
Active Online Learning for Social Media Analysis to Support Crisis Management
Data Mining--2019-2020
Abstract   
17
LMTDM17
Applying Simulated Annealing and Parallel Computing to the Mobile Sequential Recommendation
Data Mining--2019-2020
Abstract   
18
LMTDM18
Collaboratively Tracking Interests for User Clustering in Streams of Short Texts
Data Mining--2019-2020
Abstract   
19
LMTDM19
Detecting Pickpocket Suspects from Large-Scale Public Transit Records
Data Mining--2019-2020
Abstract   
20
LMTDM20
Finding Optimal Skyline Product Combinations under Price Promotion
Data Mining--2019-2020
Abstract   
21
LMTDM21
Heterogeneous Information Network Embedding for Recommendation
Data Mining--2019-2020
Abstract   
22
LMTDM22
Hierarchical Multi-Clue Modelling for POI Popularity Prediction with Heterogeneous Tourist Information
Data Mining--2019-2020
Abstract   
23
LMTDM3
K-nearest Neighbor Search by Random Projection Forests
Data Mining--2019-2020
Abstract   
24
LMTDM24
Learning Customer Behaviors for Effective Load Forecasting
Data Mining--2019-2020
Abstract   
25
LMTDM25
On Scalable and Robust Truth Discovery in Big Data Social Media Sensing Applications
Data Mining--2019-2020
Abstract   
26
LMTDM26
Privacy-Preserving Social Media Data Publishing for Personalized Ranking-Based Recommendation
Data Mining--2019-2020
Abstract   
27
LMTDM27
Ant Colony Stream Clustering: A Fast Density Clustering Algorithm for Dynamic Data Streams
Data Mining--2019-2020
Abstract   
28
LMTDM28
Predicting Consumption Patterns with Repeated and Novel Events
Data Mining--2019-2020
Abstract   
29
LMTDM29
Multi-Party High-Dimensional Data Publishing under Differential Privacy
Data Mining--2019-2020
Abstract   
30
LMTDM30
l-Injection: Toward Effective Collaborative Filtering Using Uninteresting Items
Data Mining--2019-2020
Abstract   
31
LMTDM31
Detection of fake online reviews using semi-supervised and supervised learning
Data Mining--2019-2020
Abstract   
32
LMTDM32
Collaborative Filtering-based Electricity Plan Recommender System
Data Mining--2019-2020
Abstract