Content-Based Methods for Predicting Web-Site Demographic Attributes

Demographic information plays an important role in gaining valuable insights about a web-site's user-base and is used extensively to target online advertisements and promotions. This paper investigates machine-learning approaches for predicting the demographic attributes of web-sites using information derived from their content and their hyperlinked structure and not relying on any information directly or indirectly obtained from the web-site's users. Such methods are important because users are becoming increasingly more concerned about sharing their personal and behavioral information on the Internet. Regression-based approaches are developed and studied for predicting demographic attributes that utilize different content-derived features, different ways of building the prediction models, and different ways of aggregating web-page level predictions that take into account the web's hyperlinked structure. In addition, a matrix-approximation based approach is developed fo...

• Type: Journal
• Year: 2010
• Where: ICDM
• Authors: Santosh Kabbur, Eui-Hong Han, George Karypis
• Keywords: Data Mining, Demographic Attributes, ICDM 2010, Prediction, Probability Mass Function