Effect of task on time spent reading as an implicit measure of interest

Abstract

Information Filtering systems learn user preferences either through explicit or implicit feedback. However, requiring users to explicitly rate items as part of the interface interaction can place a large burden on the user. Implicit feedback removes the burden of explicit user ratings by transparently monitoring user behavior such as time spent reading, mouse movements and scrolling behavior. Previous research has shown that task may have an impact on the effectiveness of some implicit measures. In this work we report both qualitative and quantitative results of an initial study examining the relationship between user time spent reading and relevance for three web search tasks: relevance judgment, simple question answering and complex question answering. This study indicates that the usefulness of time spent as a measure of user interest is related to task and is more useful for more complex web search tasks. Future directions for this research are presented. IntroductionThe rapid growth of the World Wide Web has highlighted the need for systems that help users sift through the wealth of information available online in order to find documents relevant to their needs. Information Filtering (IF) systems select documents for users based on their previous preferences. In order to learn user preferences, IF systems must determine user interest through either explicit or implicit user feedback. The next generation of IF systems must respond to the context of past user preferences as well as their current task, and it must do so without incurring additional overhead fiom the user.Explicit feedback may come in the form of user defined rules or more commonly as user ratings. Users are often required to give binary judgments after reading each document, such as "relevant" or "not relevant", or rate items on a five point Likert scale. Implicit feedback transparently monitors user behavior in order to determine user preferences. Common user behaviors that have been found to indicate interest include time spent reading, mouse movements, scrolling behavior and interactions with a document, such as saving, forwarding and printing.Implicit feedback has a number of advantages over explicit feedback. Unobtrusively monitoring user behavior allows users to focus on the task at hand without the interruption of having to give ratings for documents. Requiring users to stop and explicitly rate items before moving on to the next document disrupts a user's normal reading and browsing behavior (Middleton et al., 2003;Nichols, 1997) and complicates the design. It is difficult to motivate users to continuously give explicit ratings (Kim et al., 2002; Konstan et al., 1997) even when the benefits are obvious (i.e., personalized recommendations). Implicit feedback may also help to eliminate inconsistencies in explicit user ratings.A hurdle for IF systems is user attitude towards having their behavior monitored. If users are not comfortable with having some behaviors monitored in order to make recommendations then an IF system with implicit fe...

Investigating the Effect of Implicit Browsing Behaviour on Students’ Performance in a Task Specific Context

“…Keller et al [21] did not totally assert to [3], they suggest that users spend longer time on a page due to an increase in the complexity of the task. Liu et al [22] supported Keller et al [21] by adding that dwell time alone is only good for measuring factual task but it is not good for intellectual task. They also suggested that that the concept of dwell time should be developed according to the task a user is working on.…”

Implicit Client Side User Profiling for Improving Relevancy of Search Results

“…For this we sort pages in order of their relevant factors and only the top few pages (based on a threshold, to be taken from the user) are said to be relevant. The activity by the user on the webpage can be inferred by the active time spent by the user, mouse movement and scrolling behaviour on the webpage as indicated in [5] …”

Finding User’s Interest Blocks using Significant Implicit Evidence for Web Browsing on Small Screen Devices

“…Vogt [20] claimed that viewing time normalized by document length is a good predictor of relevance. Kellar et al [8] reported that time spent on reading as measure of user interest becomes more useful as the task becomes more complex. Kelly and Belkin [11] focused on document display time and demonstrated that its usefulness differs significantly according to tasks and users.…”

“…Recent researches have investigated common user behaviors and drawn several conclusions on whether implicit feedback is useful for indicating user preference and whether its quality is influenced by tasks or users [8,9,11,22]. They are primarily for Web retrieval on desktops, therefore are not directly applicable for this research.…”