Cognitive Models Of Web-navigation Research Articles

A STUDY ON THE ROLE OF NON-HYPERLINK TEXT ON WEB NAVIGATION

Cognitive models of web navigation have been used for evaluating websites and predicting user navigation behavior. Currently they predict the correct hyperlink by using information from the hyperlink text alone and ignore all other textual information on a webpage. The validity of this assumption is examined by investigating the role of non-hyperlink text on user navigation behavior. In the first experiment, we created two versions of a website by removing the non-hyperlink text from it. We found that there was no significant effect of non-hyperlink text on the user navigation behavior. Participants were equally accurate, selected the same set of pages to visit and spent the same amount of time on that common set with or without non-hyperlink text. This result validates the assumptions of those models of user-navigation behavior that consider information from the hyperlink text only. However, in a followup experiment, we included high-relevance and low-relevance pictures on the website, and repeated the experiment with and without non-hyperlink text. We found that participants were more accurate in the presence of non-hyperlink text than without it. This result suggests that the presence of pictures might prime the users to pay attention to non-hyperlink text, which increases the task accuracy.

CoLiDeS+ Pic: a cognitive model of web-navigation based on semantic information from pictures

Comprehension-based linked model of deliberate search (CoLiDeS) + Pic is a cognitive model of web-navigation that takes into account the semantic information from graphical elements present on a web-page to compute the information scent value of the hyperlinks. The model is based on CoLiDeS, which has a two-phase processing cycle: (a) attention phase, which first parses the web-page and focuses attention on the region of the web-page that is semantically most similar to the goal, and (b) action-selection phase, which evaluates the available actions in the focused region and selects a particular action such as clicking a link. The graphical elements are important both for attracting attention to a region of the web-page and for communicating semantic meaning that may alter or enhance the meaning of the hyperlink labels. In the first part of this article, we give a theoretical explanation of the CoLiDeS + Pic model and describe the methodology followed to implement it. In the second part, we run a simulation on a mock-up website and evaluate the effect of pictures on information scent of hyperlinks by means of the CoLiDeS + Pic model on basis of the simulation results. It was found that CoLiDeS + Pic with highly relevant pictures increases the values of information scent of task-relevant hyperlinks, and therefore it increases the probability of selecting those hyperlinks compared to CoLiDeS (without pictures) or CoLiDeS + Pic with lowly relevant pictures. These results confirm the importance of including information from pictures into the modelling of web-navigation.

Using a Cognitive Model of Web-Navigation to Generate Support for 3D Virtual Navigation

Though the cognitive processes controlling user navigation in virtual environments as well as in websites are similar, cognitive models of web-navigation have never been used for generating support in virtual environment navigation. We created a simulated 3D building of a hospital and presented users various navigation tasks under two conditions: a control condition and a model-generated support condition. Participants with model-generated support participants took significantly less time to reach their destination and were significantly less disoriented. The impact of model-generated support on disorientation was especially higher for users with low spatial ability.

Evaluating CoLiDeS + Pic: the role of relevance of pictures in user navigation behaviour

CoLiDeS + Pic is a cognitive model of web-navigation that incorporates semantic information from pictures intoCoLiDeS. In our earlier research, we have demonstrated that by incorporating semantic information from pictures, CoLiDeS + Pic can predict the hyperlinks on the shortest path more frequently, and also with greater information scent, compared to earlier cognitive models of web-navigation like CoLiDeS that relied only on textualinformation from hyperlinks. In this article, we investigate the following research questions. First, would the increase in information scent have an impact on the actual user navigation behaviour? Second, do users actually follow the navigation path predicted by CoLiDeS + Pic? In other words, would CoLiDeS + Pic predict actual user navigation behaviour more accurately than CoLiDeS? We investigate these questions by varying the relevance of pictures on aweb page and studying the impact of varying relevance on the user navigation patterns. We found that under the highly relevant picture condition, users were more accurate and took less time to finish their tasks. Also, under thehighly relevant picture condition, CoLiDeS + Pic predicts significantly greater number of actual user clicks. There was no significant difference in model predictions between the lowly relevant picture condition and no-picture condition. These results validate the predictions made by CoLiDeS + Pic.

Embedding semantic information from pictures into cognitive modeling of web-navigation

Several attempts at cognitive modeling of web-navigation behaviour (SNIF-ACT, MESA, CoLiDeS, CoLiDeS+) have focused entirely on the semantic information derived from textual elements and repeatedly ignored the role played by graphical and visual information. While research on visual search has emphasized the efficiency of our visual system at perceiving salient objects, there have been no attempts at including information from the visual modality into cognitive models of web-navigation. This paper discusses a new approach to include semantic information from pictures into cognitive models of web-navigation and verifies its accuracy with a simulation done on a mock-up website. Results show that the optimal links that should be chosen to find the requested information are predicted more often and with greater information scent by this extended model than by the CoLiDeS model.

Using a cognitive model to generate web navigation support

A computational cognitive model of web navigation is proposed. Based on theories and models of text comprehension and web navigation, the plausibility of the proposed model is discussed. The model was used to generate navigation support and this support was offered to users in real time during their navigation sessions, in two experiments. In the first experiment navigation support was offered in the auditory modality and it had a positive effect on user's task performance, especially for users with low spatial abilities. In the second experiment navigation support was offered in the visual modality and users positively evaluated it. Users navigated in a more structured way, judged the system as more usable, and perceived themselves as less disoriented. Support did also here lead to better task performance. Finally, some aspects concerning further enhancement of the validity of the proposed model and its practical relevance are discussed.