Web Spam Detection using ANN – Dissertation Report

Description

Web Spam Detection using Supervised Learning of Artificial Neural Network – Thesis Report

Visual Studio 2010 Project – M. Tech Dissertation Report

Content:

• Full Source Code – C# Visual Studio 2010 Project
• Thesis Report File (.docx)
• MS SQL Server 2008 R2 DataBase file
• PowerPoint Presentation (.PPTx)

Level: Medium/Graduate Level/Academic Project

Features:

• A comparison of three Artificial Neural Network Algorithms.
  • Conjugate Gradient learning algorithm,
  • Resilient Back-propagation algorithm, and
  • Levenberg-Marquardt algorithm.
• All of these are Supervised Learning Algorithms.
• Our work evaluates these algorithms on the basis of classification results as well as computational requirements in training.
• The domain under which these algorithms are used is web spam classification.
• Our work also includes the development of a lightweight classifier and analysis of search engine results in the context of spamdexing.

Note:

• As it is an academic project, some features may not work as expected. 
• Accept the project as it is. Make necessary changes according to your need.
• There is no support on how to run or for debugging.
• On the test machine, the project was successfully running.
• For any query contact by email: info@thedigimart.in