Implicit Predictive Indicators: Mouse Activity and Dwell Time

Abstract : Humans vary in their learning behaviour. It is difficult to predict the actual needs of learners through their search activity. It is also difficult to predict accurately the level of satisfaction after the learner finds a perceived relevant document. This research is a preliminary study to examine the predictive strength of some implicit indicators on web documents. An automated study was carried out and 13 participants were given 15 short documents to read and rate according to their perception of relevance to a given topic area. An investigation was carried out to examine if there exists a correlation between user generated implicit indicators and the explicit ratings. The findings show that there is a positive correlation between the dwell time and user explicit ratings. Although there was no significant correlation between mouse movement/distance and user explicit rating, there was a relationship between the homogeneous clusters of the implicit indicators and the user ratings.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.162-171, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_16〉
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Stephen Akuma, Chrisina Jayne, Rahat Iqbal, Faiyaz Doctor. Implicit Predictive Indicators: Mouse Activity and Dwell Time. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.162-171, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_16〉. 〈hal-01391311〉

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