Difference between revisions of "Listing Page Classifier"
| Line 23: | Line 23: | ||
===Approaches (IN PROGRESS)=== | ===Approaches (IN PROGRESS)=== | ||
[[Listing Page Classifier Progress|Progress Log(updated on 4/4/2019)]] | [[Listing Page Classifier Progress|Progress Log(updated on 4/4/2019)]] | ||
| − | * | + | * Finding all internal links of a webpage |
#BFS approach | #BFS approach | ||
| − | E:\projects\listing page identifier\Internal_Link\ | + | E:\projects\listing page identifier\Internal_Link\Internal_url_BFS.py |
#DFS approach(IN PROGRESS) | #DFS approach(IN PROGRESS) | ||
| + | E:\projects\listing page identifier\Internal_Link\Internal_url_DFS.py | ||
===Image Processing=== | ===Image Processing=== | ||
This method would likely rely on a [https://en.wikipedia.org/wiki/Convolutional_neural_network convolutional neural network (CNN)] to classify HTML elements present in web page screenshots. Implementation could be achieved by combining the VGG16 model or ResNet architecture with batch normalization to increase accuracy in this context. | This method would likely rely on a [https://en.wikipedia.org/wiki/Convolutional_neural_network convolutional neural network (CNN)] to classify HTML elements present in web page screenshots. Implementation could be achieved by combining the VGG16 model or ResNet architecture with batch normalization to increase accuracy in this context. | ||
Revision as of 14:25, 8 April 2019
| Listing Page Classifier | |
|---|---|
| Project Information | |
| Has title | Listing Page Classifier |
| Has owner | Nancy Yu |
| Has start date | |
| Has deadline date | |
| Has project status | Active |
| Copyright © 2019 edegan.com. All Rights Reserved. | |
Summary
The objective of this project is to determine which web page on an incubator's website contains the client company listing.
The project will ultimately use data (incubator names and URLs) identified using the Ecosystem Organization Classifier (perhaps in conjunction with an additional website finder tool, if the Incubator Seed Data source does not contain URLs). Initially, however, we are using accelerator websites taken from the master file from the U.S. Seed Accelerators project.
We are building three tools: a site map generator, a web page screenshot tool, and an image classifier. Then, given an incubator URL, we will find and generate (standardized size) screenshots of every web page on the website, code which page is the client listing page, and use the images and the coding to train our classifier. We currently plan to build the classifier using a convolutional neural network (CNN), as these are particularly effective at image classification.
Current Work
Main Tasks
- Build a site map generator: output every internal link of input websites
- Build a tool that captures a screenshot of individual web pages
- Build a CNN classifier using Python and TensorFlow
Approaches (IN PROGRESS)
Progress Log(updated on 4/4/2019)
- Finding all internal links of a webpage
- BFS approach
E:\projects\listing page identifier\Internal_Link\Internal_url_BFS.py
- DFS approach(IN PROGRESS)
E:\projects\listing page identifier\Internal_Link\Internal_url_DFS.py
Image Processing
This method would likely rely on a convolutional neural network (CNN) to classify HTML elements present in web page screenshots. Implementation could be achieved by combining the VGG16 model or ResNet architecture with batch normalization to increase accuracy in this context.
