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

Cognitive models of web navigation have been used for evaluating websitesand predicting user navigation behavior. Currently they predict the correcthyperlink by using information from the hyperlink text alone and ignore allother textual information on a webpage. The validity of this assumption isexamined by investigating the role of non-hyperlink text on user navigationbehavior. In the first experiment, we created two versions of a website byremoving the non-hyperlink text from it. We found that there was no significanteffect of non-hyperlink text on the user navigation behavior. Participants wereequally accurate, selected the same set of pages to visit and spent the sameamount of time on that common set with or without non-hyperlink text. Thisresult validates the assumptions of those models of user-navigation behaviorthat consider information from the hyperlink text only. However, in a followupexperiment, we included high-relevance and low-relevance pictures on thewebsite, and repeated the experiment with and without non-hyperlink text.We found that participants were more accurate in the presence of non-hyperlinktext than without it. This result suggests that the presence of pictures mightprime the users to pay attention to non-hyperlink text, which increases the taskaccuracy

On the evolution of hyperlinking

Across time, the hyperlink object has supported different applications and studies. This is one perspective on the evolution of the hyperlinking concept, its context and related behaviors. Through a spectrum of hyperlinking applications and practices, the article contrasts the status quo with its related, broader, conceptual roots; it also bridges to some theorized and prototyped hyperlink variations, namely "stigmergic hyperlinks", to make the case that the ubiquitousness of some objects and certain usage patterns can obfuscate opportunities to (re)think them. In trying to contribute an answer to "what has the common hyperlink (such an apparently simple object) done to society, and what has society done to it?", the article identifies situations that have become so embedded in the daily routine, that it is now hard to think of hyperlinking alternatives.info:eu-repo/semantics/publishedVersio

Staging Transformations for Multimodal Web Interaction Management

Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations -- a theory for representing and reasoning about dialogs based on partial input. It supports multiple interaction interfaces, and offers sessioning, caching, and co-ordination functions through the use of an interaction manager. Two case studies are presented to illustrate the promise of this approach.Comment: Describes framework and software architecture for multimodal web interaction managemen

Mining Missing Hyperlinks from Human Navigation Traces: A Case Study of Wikipedia

Hyperlinks are an essential feature of the World Wide Web. They are especially important for online encyclopedias such as Wikipedia: an article can often only be understood in the context of related articles, and hyperlinks make it easy to explore this context. But important links are often missing, and several methods have been proposed to alleviate this problem by learning a linking model based on the structure of the existing links. Here we propose a novel approach to identifying missing links in Wikipedia. We build on the fact that the ultimate purpose of Wikipedia links is to aid navigation. Rather than merely suggesting new links that are in tune with the structure of existing links, our method finds missing links that would immediately enhance Wikipedia's navigability. We leverage data sets of navigation paths collected through a Wikipedia-based human-computation game in which users must find a short path from a start to a target article by only clicking links encountered along the way. We harness human navigational traces to identify a set of candidates for missing links and then rank these candidates. Experiments show that our procedure identifies missing links of high quality

Local Ranking Problem on the BrowseGraph

The "Local Ranking Problem" (LRP) is related to the computation of a centrality-like rank on a local graph, where the scores of the nodes could significantly differ from the ones computed on the global graph. Previous work has studied LRP on the hyperlink graph but never on the BrowseGraph, namely a graph where nodes are webpages and edges are browsing transitions. Recently, this graph has received more and more attention in many different tasks such as ranking, prediction and recommendation. However, a web-server has only the browsing traffic performed on its pages (local BrowseGraph) and, as a consequence, the local computation can lead to estimation errors, which hinders the increasing number of applications in the state of the art. Also, although the divergence between the local and global ranks has been measured, the possibility of estimating such divergence using only local knowledge has been mainly overlooked. These aspects are of great interest for online service providers who want to: (i) gauge their ability to correctly assess the importance of their resources only based on their local knowledge, and (ii) take into account real user browsing fluxes that better capture the actual user interest than the static hyperlink network. We study the LRP problem on a BrowseGraph from a large news provider, considering as subgraphs the aggregations of browsing traces of users coming from different domains. We show that the distance between rankings can be accurately predicted based only on structural information of the local graph, being able to achieve an average rank correlation as high as 0.8

¿Cómo navegan los adolescentes en Wikipedia para contestar preguntas?

In one experiment, we explored how high school students use hyperlink relevance cues while they navigate to answer questions from hypertexts. Current evidence has shown that students may navigate by either performing a deep semantic analysis of the relationship between the question and the existing hyperlinks, or by matching words in the question to words in the hyperlink labels. We focused on how students combine both cues during navigation, and how comprehension skills relate to the use of such cues. Our study revealed that 14 year old students (N = 53) selected hyperlinks by relying to a similar degree on both word matching and semantic overlap. Furthermore, when there was a conflict between an irrelevant link cued via word matching and a relevant link only cued through semantic overlap, students\u27 comprehension skills facilitated their initial selection of an informative relevant link. To conclude, we discuss the implications of these results for current models of hypertext navigation. (DIPF/Orig.

Text books untuk mata kuliah pemrograman web

.HTML.And.Web.Design.Tips.And.Techniques.Jan.2002.ISBN.0072228253.pd