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Proceedings ArticleDOI

Inferring Web Page Relevancy through Keyboard and Mouse Usage

TLDR
This paper pre-set a framework of how to analyse the user behaviour through his mouse and keyboard usage and suggests how these activities can be inferred as implicit interest indicators.
Abstract
We live in the society in which Computers and the Web are widely used for accessing all kinds of information. The user accesses the web primarily through a web browser. All the user behaviour on his browser (like Navigation, Print, Bookmark, Save) can be tracked to infer the interest of the user. Analysing the user's behaviour while browsing web pages can be done by monitoring the keyboard and mouse usage. These behaviour activities are user interest indicators too, if interpreted correctly. A lot of research has been done on various Implicit and Explicit interest indicators in User Profiling but very few are specific to the users' keyboard and mouse usage. The users' behaviour can be extensively investigated to infer user interest on web pages. In this paper we pre-set a framework of how to analyse the user behaviour through his mouse and keyboard usage. We go on to suggest how these activities can be inferred as implicit interest indicators. These web activities reveal a lot about the user and the relevancy of the web page to the user can be computed by using his keyboard and mouse usage.

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Citations
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Book ChapterDOI

Software Analytics for Web Usability: A Systematic Mapping

TL;DR: It is found that most studies are focused on tools for capturing information on user’s navigation, however, few tools have presented mechanisms for visualization of these user interaction data.
Book ChapterDOI

Simple Mouse Attribute Analysis

TL;DR: The objective of this study was to point out a new interesting research direction of using implicit gathered user data from one of the default communication channels in HCI: the computer mouse.
References
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Proceedings ArticleDOI

Implicit interest indicators

TL;DR: It was found that the time spent on a pages, the amount of scrolling on a page and the combination of time and scrolling had a strong correlation with explicit interest, while individual scrolling methods and mouse-clicks were ineffective in predicting explicit interest.
Proceedings ArticleDOI

Learning users' interests by unobtrusively observing their normal behavior

TL;DR: This work presents an approach that circumvents the need for human-labeled pages by learning “surrogate” tasks where the desired output is easily measured, such as the number of hyperlinks clicked on a page or the amount of scrolling performed.
Proceedings ArticleDOI

Cheese: tracking mouse movement activity on websites, a tool for user modeling

TL;DR: A straightforward way to record all mouse movements on a page is developed and certain mouse behaviors are found, common across many users, which are useful for content providers in increasing the effectiveness of their interface design.
Proceedings ArticleDOI

A comparison of voice controlled and mouse controlled web browsing

TL;DR: The study shows that voice control adds approximately 50% to the performance time for certain types of tasks and subjective satisfaction measures indicate that for voice browsing, textual links are preferable to numbered links.
Proceedings ArticleDOI

Navigating documents with the virtual scroll ring

TL;DR: This work presents a technique for scrolling through documents that is simple to implement and requires no special hardware, accomplished by simulating a hardware scroll ring--a device that maps circular finger motion into vertical scrolling.
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