Paper Title
A Global Flow-Based Technique For Analysis Of Inherent Interaction On Wikipedia

These documents address how to improve a website without introducing significant changes. Specifically, we propose a mathematical programming model to improve the user steering on a website while minimize alteration to its current structure. Results from extensive tests conducted on a publicly available real data set indicate that our model not only significantly improves the user steering with very few changes, but also can be successfully solved. We have also tested the model on large synthetic data sets to display that it scales up very well. In addition, we define two evaluation metrics and use them to assess the presentation of the improved website using the real data set. Evaluation results confirm that the user steering on the improved structure is indeed greatly enhanced. More interestingly, we find that heavily disoriented users are more likely to benefit from the improved arrangement than the less disoriented users. We propose a new method using a worldwide maximum flow which reflects all the three factors and does not underestimate objects having high degree. We confirm through experiments that our method can measure the strength of a relationship more appropriately than these previously proposed methods do. Another remarkable aspect of our method is mining elucidatory objects, that is, objects constitute a relationship. We explain that mining elucidatory objects would open a novel way to deeply understand a relationship.