Guided tours and tabletops: tools for communicating in a hypertext environment
ACM Transactions on Information Systems (TOIS)
Orienteering in an information landscape: how information seekers get from here to there
INTERCHI '93 Proceedings of the INTERCHI '93 conference on Human factors in computing systems
Using information scent to model user information needs and actions and the Web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Transparent Queries: investigation users' mental models of search engines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
How knowledge workers use the web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ScentTrails: Integrating browsing and searching on the Web
ACM Transactions on Computer-Human Interaction (TOCHI)
The perfect search engine is not enough: a study of orienteering behavior in directed search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Large scale analysis of web revisitation patterns
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Mining the search trails of surfing crowds: identifying relevant websites from user activity
Proceedings of the 17th international conference on World Wide Web
Introduction to Information Retrieval
Introduction to Information Retrieval
Models of searching and browsing: languages, studies, and applications
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Wikispeedia: an online game for inferring semantic distances between concepts
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Studying trailfinding algorithms for enhanced web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Assessing the scenic route: measuring the value of search trails in web logs
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Pragmatic evaluation of folksonomies
Proceedings of the 20th international conference on World wide web
Communications of the ACM
Navigational efficiency of broad vs. narrow folksonomies
Proceedings of the 23rd ACM conference on Hypertext and social media
Proceedings of the 23rd ACM conference on Hypertext and social media
Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies
Models of human navigation in information networks based on decentralized search
Proceedings of the 24th ACM Conference on Hypertext and Social Media
The last click: why users give up information network navigation
Proceedings of the 7th ACM international conference on Web search and data mining
Finding progression stages in time-evolving event sequences
Proceedings of the 23rd international conference on World wide web
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Navigating information spaces is an essential part of our everyday lives, and in order to design efficient and user-friendly information systems, it is important to understand how humans navigate and find the information they are looking for. We perform a large-scale study of human wayfinding, in which, given a network of links between the concepts of Wikipedia, people play a game of finding a short path from a given start to a given target concept by following hyperlinks. What distinguishes our setup from other studies of human Web-browsing behavior is that in our case people navigate a graph of connections between concepts, and that the exact goal of the navigation is known ahead of time. We study more than 30,000 goal-directed human search paths and identify strategies people use when navigating information spaces. We find that human wayfinding, while mostly very efficient, differs from shortest paths in characteristic ways. Most subjects navigate through high-degree hubs in the early phase, while their search is guided by content features thereafter. We also observe a trade-off between simplicity and efficiency: conceptually simple solutions are more common but tend to be less efficient than more complex ones. Finally, we consider the task of predicting the target a user is trying to reach. We design a model and an efficient learning algorithm. Such predictive models of human wayfinding can be applied in intelligent browsing interfaces.