Improving Web Navigation Usability by Comparing Actual and Anticipated Usage - 2015 PROJECT TITLE: Improving Web Navigation Usability by Comparing Actual and Anticipated Usage - 2015 ABSTRACT: We tend to gift a replacement methodology to identify navigation-related.Net usability issues based on comparing actual and anticipated usage patterns. The actual usage patterns can be extracted from.Net server logs routinely recorded for operational websites by first processing the log knowledge to identify users, user sessions, and user task-oriented transactions, and then applying an usage mining algorithm to discover patterns among actual usage methods. The anticipated usage, including info regarding each the trail and time required for user-oriented tasks, is captured by our ideal user interactive path models created by cognitive consultants based on their cognition of user behavior. The comparison is performed via the mechanism of take a look at oracle for checking results and identifying user navigation difficulties. The deviation knowledge made from this comparison will help us discover usability issues and counsel corrective actions to enhance usability. A software tool was developed to automate a significant half of the activities concerned. With an experiment on a little service-oriented website, we tend to identified usability problems, that were cross-validated by domain experts, and quantified usability improvement by the higher task success rate and lower effort and time for given tasks after suggested corrections were implemented. This case study provides an initial validation of the applicability and effectiveness of our methodology. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Web Mining Projects Network-Based Modeling and Intelligent Data Mining of Social Media for Improving Care - 2015 Constructing Query-Driven Dynamic Machine Learning Model With Application to Protein-Ligand Binding Sites Prediction - 2015