Computationally Assessing the Visual Quality of a Web Page

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  • Topic: Support vector machine, Machine learning, Data
  • Pages : 6 (1727 words )
  • Download(s) : 97
  • Published : November 12, 2012
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FINAL YEAR PROJECT INTERIM REPORT

COMPUTATIONALLY ASSESSING THE VISUAL QUALITY OF A WEB PAGE
(A3147-121)

Supervised by Submitted by

: Prof. Wang Gang : Aparna Janardhanan Nambiar U0920595J IEM/4

TABLE OF CONTENTS
Table of Figures ................................................................................................................................................................. 2 Abstract ................................................................................................................................................................................ 3 1. Introduction .................................................................................................................................................................. 4 2. Literature Review ........................................................................................................................................................ 5 3. Methodology ................................................................................................................................................................. 7 3.1. Database collection ........................................................................................................................................ 7 3.2. Feature extraction .......................................................................................................................................... 7 3.3. Obtaining the Codebook and the Kernal Matrix ................................................................................ 7 3.4. Manipulating the testing data.................................................................................................................... 8 4. Future Work ................................................................................................................................................................... 9 4.1. Plan of Action ................................................................................................................................................... 9 .......................................................................................................................................................................................... 10

TABLE OF FIGURES
Figure 1 : Comparison between the predicted and human labelled scores for webpages collected from various years. .......................................................................................................................................................... 5 Figure 2 : Project plan for semester 1. Blue column represents the current progress in the project. ............................................................................................................................................................................... 10 Figure 3 : Project plan for semester 2. .................................................................................................................. 11

ABSTRACT
This report describes the progress the author has made on her Final year Project from August 2012 - November 2012. The report also briefly explains the project topic, future work and project plan for the following semester. The purpose of this project is to build an algorithm to evaluate a web page’s visual quality and appearance. For this a database of 113 webpages and 101 webpages were collected for training and test respectively. The training dataset’s webpages were classified into aesthetically appealing and non-appealing based on ground truth. Image features were extracted from the training dataset. According to these features an image classifier was to be obtained using SVN technique. Unknown and new webpages will be tested and subjected to prediction regarding its aesthetic appearance based on this classifier.

1. INTRODUCTION

The content on a website becomes information only when the brain cognitively processes it. But the very first...
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