https://github.com/ozlemkorpe/dm-clustering-techniques-on-transportation-dataset

Data mining clustering techniques; k-means, dbscan and hierarchical clustering are applied on Antalya bus transportation dataset by using Knime environment.
https://github.com/ozlemkorpe/dm-clustering-techniques-on-transportation-dataset

clustering clustering-algorithm data-mining knime knime-analytics-platform

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Data mining clustering techniques; k-means, dbscan and hierarchical clustering are applied on Antalya bus transportation dataset by using Knime environment.

• Host: GitHub
• URL: https://github.com/ozlemkorpe/dm-clustering-techniques-on-transportation-dataset
• Owner: ozlemkorpe
• Created: 2020-07-19T02:16:06.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-08-07T13:24:28.000Z (about 5 years ago)
• Last Synced: 2025-05-22T08:18:56.170Z (5 months ago)
• Topics: clustering, clustering-algorithm, data-mining, knime, knime-analytics-platform
• Homepage:
• Size: 7.66 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# DM-Clustering-Techniques-on-Transportation-Dataset

Data mining clustering techniques; k-means, dbscan and hierarchical clustering are applied on Antalya bus transportation dataset.

![Complete Workflow](https://github.com/ozlemkorpe/DM-Clustering-Techniques-on-Transportation-Dataset/blob/master/screenshots/complete-workflow.png)

This project was built using [Knime](https://www.knime.com/).

## Columns

- **Linename**: Name of the bus line. 

- **Lineid**: Unique ID's of lines.

- **Route**: Name of the bus route.

- **Routeid**: ID of the bus route. Each route has unique ID.

- **Stopname**: Name of the bus stop.

- **Stopid**: Unique ID of bus stop.

- **StopSequence**: Visit sequence of the bus for each stop.

## Usage

All files are excluded from Knime environment, they must be opened by using Knime. Necessary dataset can also be found in the Dataset folder and destination of the dataset must be reconfigured in file reader node.

## Grouping Operations

GroupBy node is used for grouping bus routes with count of bus stops it passing by, finding possible bus stations by grouping bus stops by its stop sequences, finding most and least used bus stops.

## Similarity Search

String distances are calculated for line and stopnames by using String Distances node and aggregated by using Aggregated Distance node. By using Similarity Search node, similar row analyzed.

## Clustering Techniques

Clustering techniques are used for clustering bus routes with its similarity. Bus routes which passing by more common bus stops are accepted as similar.

### K-Means Clustering

![K-Means Clustering Results](https://github.com/ozlemkorpe/DM-Clustering-Techniques-on-Transportation-Dataset/blob/master/screenshots/kmeans.png)

### DB-Scan Clustering

![DBScan Clustering Results](https://github.com/ozlemkorpe/DM-Clustering-Techniques-on-Transportation-Dataset/blob/master/screenshots/dbscan.png)

### Hierarchical Clustering

![Hierarchical Clustering Results](https://github.com/ozlemkorpe/DM-Clustering-Techniques-on-Transportation-Dataset/blob/master/screenshots/hierarchical.png)

## Performance Evaluation

![Time Performances](https://github.com/ozlemkorpe/DM-Clustering-Techniques-on-Transportation-Dataset/blob/master/screenshots/performancetime.png)

## Map Viewer

## Authors

* **Özlem Körpe** - *Initial work* - [ozlemkorpe](https://github.com/ozlemkorpe)