Suggest a mini project
Hiiiiii.,.....
Hello everyone...Now I am persuing my B tech (Computer Science) 3rd year.. ๐ And In 4-1, I have a mini project...There are so many project ideas in this thread..But i am confusing ๐ to choose one of them ๐ ..Can you suggest me an idea for a mini project..Its should be interesting for everyone...I dont have any interest about a particular subject...So, please anyone can suggest me......... ๐
WINNERS DONT DO DIFFERENT THINGS..THEY DO THINGS DIFFERENTLY...
Hello everyone...Now I am persuing my B tech (Computer Science) 3rd year.. ๐ And In 4-1, I have a mini project...There are so many project ideas in this thread..But i am confusing ๐ to choose one of them ๐ ..Can you suggest me an idea for a mini project..Its should be interesting for everyone...I dont have any interest about a particular subject...So, please anyone can suggest me......... ๐
WINNERS DONT DO DIFFERENT THINGS..THEY DO THINGS DIFFERENTLY...
Replies
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jhbalajiHow about these they all deal with data mining mate
- Rank Aggregation for Automatic Schema Matching
- Rule Extraction from Support Vector Machines: A Sequential Covering Approach
- Efficient Computation of Iceberg Cubes by Bounding Aggregate Functions
- A Note on Linear Time Algorithms for Maximum Error Histograms
- Toward Exploratory Test-Instance-Centered Diagnosis in High-Dimensional Classification
- An Entropy Weighting k-Means Algorithm for Subspace Clustering of High-Dimensional Sparse Data
- A Method for Estimating the Precision of Place name Matching
- Efficiently Querying Large XML Data Repositories: A Survey
- Graph-Based Analysis of Human Transfer Learning Using a Game Tested
- Evaluating Universal Quantification in XML
- Customer Profiling & Segmentation using Data Mining Techniques
- Efficient Frequent Item set Mining Using Global Profit Weighted (GPW) Support Threshold
- Fast Algorithms for Frequent Item set Mining using FP-Trees
- Mining Confident Rules without Support Requirement
- Mining Frequent Item set without Support Threshold
- unified framework for utility based measures
- An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval
- The Google Similarity Distance
- Reverse Nearest Neighbors Search in Ad Hoc Subspaces
- Quality-Aware Sampling and Its Applications in Incremental Data Mining
- An Exact Data Mining Method for Finding Center Strings and All Their Instances
- Negative Samples Analysis in Relevance Feedback
- Bayesian Networks for Knowledge-Based Authentication
- Continuous Nearest Neighbor Queries over Sliding Windows
- The Concentration of Fractional Distances
- Efficient Approximate Query Processing in Peer-to-Peer Networks
- Ontology-Based Service Representation and Selection
- Compressed Hierarchical Mining of Frequent Closed Patterns from Dense Data Sets
- Semi-supervised Regression with Co-training-Style Algorithms
- Evaluation of Clustering with Banking Credit Card segment
- An efficient clustering algorithm for huge dimensional database
- Novel approach for Targeted Association Querying
- Hiding Sensitive Association Rules with Limited Side Effects
- A Relation-Based Search Engine in Semantic Web
- Classifier Ensembles with a Random Linear Oracle
- An Efficient Web Page Change Detection System Based on an Optimized Hungarian Algorithm
- Mining Nonambiguous Temporal Patterns for Interval-Based Events
- Peer-to-Peer in Metric Space and Semantic Space
- Adaptive Index Utilization in Memory-Resident Structural Joins
- On Three Types of Covering-Based Rough Sets
-
Sahithi PallavijhbalajiHow about these they all deal with data mining mate
- Rank Aggregation for Automatic Schema Matching
- Rule Extraction from Support Vector Machines: A Sequential Covering Approach
- Efficient Computation of Iceberg Cubes by Bounding Aggregate Functions
- A Note on Linear Time Algorithms for Maximum Error Histograms
- Toward Exploratory Test-Instance-Centered Diagnosis in High-Dimensional Classification
- An Entropy Weighting k-Means Algorithm for Subspace Clustering of High-Dimensional Sparse Data
- A Method for Estimating the Precision of Place name Matching
- Efficiently Querying Large XML Data Repositories: A Survey
- Graph-Based Analysis of Human Transfer Learning Using a Game Tested
- Evaluating Universal Quantification in XML
- Customer Profiling & Segmentation using Data Mining Techniques
- Efficient Frequent Item set Mining Using Global Profit Weighted (GPW) Support Threshold
- Fast Algorithms for Frequent Item set Mining using FP-Trees
- Mining Confident Rules without Support Requirement
- Mining Frequent Item set without Support Threshold
- unified framework for utility based measures
- An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval
- The Google Similarity Distance
- Reverse Nearest Neighbors Search in Ad Hoc Subspaces
- Quality-Aware Sampling and Its Applications in Incremental Data Mining
- An Exact Data Mining Method for Finding Center Strings and All Their Instances
- Negative Samples Analysis in Relevance Feedback
- Bayesian Networks for Knowledge-Based Authentication
- Continuous Nearest Neighbor Queries over Sliding Windows
- The Concentration of Fractional Distances
- Efficient Approximate Query Processing in Peer-to-Peer Networks
- Ontology-Based Service Representation and Selection
- Compressed Hierarchical Mining of Frequent Closed Patterns from Dense Data Sets
- Semi-supervised Regression with Co-training-Style Algorithms
- Evaluation of Clustering with Banking Credit Card segment
- An efficient clustering algorithm for huge dimensional database
- Novel approach for Targeted Association Querying
- Hiding Sensitive Association Rules with Limited Side Effects
- A Relation-Based Search Engine in Semantic Web
- Classifier Ensembles with a Random Linear Oracle
- An Efficient Web Page Change Detection System Based on an Optimized Hungarian Algorithm
- Mining Nonambiguous Temporal Patterns for Interval-Based Events
- Peer-to-Peer in Metric Space and Semantic Space
- Adaptive Index Utilization in Memory-Resident Structural Joins
- On Three Types of Covering-Based Rough Sets
Oh....all these are the project ideas about datamining>........๐๐๐๐๐๐๐๐๐๐๐๐๐๐
WINNERS DONT DO DIFFERENT THINGS...THEY DO THINGS DIFFRENTLY...
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