This paper presents the design and user evaluation of SmartBack, a feature that complements the standard Back button by enabling users to jump directly to key pages in their navigation session, making common navigation activities more efficient. Defining key pages was informed by the findings of a user study that involved detailed monitoring of Web usage and analysis of Web browsing in terms of navigation trails. The pages accessible through SmartBack are determined automatically based on the structure of the user’s navigation trails or page association with specific user’s activities, such as search or browsing bookmarked sites. We discuss implementation decisions and present results of a usability study in which we deployed the SmartBack prototype and monitored usage for a month in both corporate and home settings. The results show that the feature brings qualitative improvement to the browsing experience of individuals who use it.

Current user interfaces for Web search, including browsers and search engine sites, typically treat search as a transient activity. However, people often conduct complex, multiquery investigations that may span long durations and may be interrupted by other tasks. In this paper, we first present the results of a survey of users ’ search habits, which show that many search tasks span long periods of time. We then introduce SearchBar, a system for proactively and persistently storing query histories, browsing histories, and users ’ notes and ratings in an interrelated fashion. SearchBar supports multi-session investigations by assisting with task context resumption and information refinding. We describe a user study comparing use of SearchBar to status-quo tools such as browser histories, and discuss our findings, which show that users find SearchBar valuable for task reacquisition. Our study also reveals the strategies employed by users of status-quo tools for handling multi-query, multi-session search tasks. Author Keywords Web search interfaces, Web history, persistent search.

Conducting research using the web is often an iterative process of collecting, comparing and contrasting information. Not surprisingly, web-based research tasks habitually span multiple web sessions and involve considerable web page revisitation. Such tasks are not only carried out by researchers, but also by casual web users who, for example, plan vacations and large purchases. Despite the prominence of this activity among web users, existing tools support it poorly. We propose an alternative approach, whereby web-based research tasks are facilitated by a web workspace which represents collected URLs with web page thumbnails. A prototype of our design was developed and studied in an evaluation with 12 participants. Each of the participants adopted the workspace approach instinctively: the workspace was used for web page revisitation, web page comparison, collection overview, cross-session task continuation, and continuous task focus.

A new method for generating trails from a person’s movement through a virtual environment (VE) is described. The method is entirely automatic (no user input is needed), and uses string-matching to identify similar sequences of movement and derive the person’s primary trail. The method was evaluated in a virtual building, and generated trails that substantially reduced the distance participants traveled when they searched for target objects in the building 5-8 weeks after a set of familiarization sessions. Only a modest amount of data (typically five traversals of the building) was required to generate trails that were both effective and stable, and the method was not affected by the order in which objects were visited. The trail generation method models an environment as a graph and, therefore, may be applied to aiding navigation in the real world and information spaces, as well as VEs. GENERATING TRAILS AUTOMATICALLY 3 1

Abstract—The current search engine model considers users not trustworthy, so no tools are provided to let them specify what they are looking for or in what context, which severely limits what they are able to achieve. Instead, search engines try to guess that, which is currently done using “implicit feedback”. In this paper we propose a “web exploration engine ”- a model where users can use the search engine as their tool and explicitly specify the context of their search. Information about the web has been pre-classified in a large number of categories; users can explore this hierarchy by providing relevance feedback or search within a particular category. Search is truly “local ” in the sense that keyword relevance

User Activities on the Web Routine activities that users perform on the Web result in the revisitation of sites and pages. Standard browser applications provide limited support for this type of habitual behaviour. They typically expose collections of visited URLs that are automatically recorded by the system, for example the navigation history, or those manually created by the user, such as bookmarks. Studies have shown that these approaches are not very successful in supporting the user in site or page revisitation. Informed by the findings of our user research and analysis of the user navigation logs, we designed SmartFavourites, a browser feature that automatically exposes candidate URLs for revisitation, in a context sensitive manner. In this paper we describe and evaluate the algorithms that we use to model the user’s habitual behaviour. We demonstrate that the use of a structured navigation history model, which essentially captures the domain specific features, facilitates the discovery of relevant usage patterns and predictive algorithms that are applicable to relatively small sizes of personal navigation history.

High percentage of Web access are visits to pages that the user has already seen in the past. Currently available support for page revisitation, through standard browser features, and suggested improvements have been based on simple history models which do not fully incorporate information about the user’s interaction with the Web and the resulting navigation structure. In our research we propose a syntax for parsing navigation history into structural elements that has proven useful for identifying patterns in the history and building features for supporting habitual Web usage. This approach is motivated by our exploratory user observation study which revealed the need for effective revisitation of key pages in the short navigation history and for supporting user in recurring Web activities observed over the long term history. We designed SmartNavigation features that address both scenarios and evaluate their usefulness through a contextual user study. Findings of the study provide further guidelines for designing revisitation support and validate the history model that we advocate. Author Keywords Web revisitation, navigation structure, navigation history,

do people find information on a familiar website?

Abstract not found