Methodology for Preprocessing and Evaluating the Time Spent on Web Pages
Peter I. Hofgesang · 2006
On the Web, the intention of a user is mostly hidden. To approximate user intention and characterise user behaviour researches in Web usage mining mainly exploit two types of information: order and frequency of visited pages. However, several studies in information retrieval and human-computer interaction have suggested that the time spent on Web pages (TSP) is an important measure of user intention and page relevance. In our paper we provide a methodology to preprocess the TSP. In addition, we present a real-world testbed that provides an unbiased environment and representative, real-world data in specific Web domains. The environment can be used to evaluate user interest indicators and importance measures, to validate clustering algorithms and for a broad selection of other validation problems. As a case study, we define a testbed on online retail shop data and evaluate, among others, the relevance of TSP