@article{Shimonishi_Kawashima_2020, title={A two-step approach for interest estimation from gaze behavior in digital catalog browsing}, volume={13}, url={https://bop.unibe.ch/JEMR/article/view/JEMR.13.1.4}, DOI={10.16910/jemr.13.1.4}, abstractNote={<div class="page" title="Page 1"> <div class="section" style="background-color: rgb(100.000000%, 100.000000%, 100.000000%);"> <div class="layoutArea"> <div class="column"> <p><span style="font-size: 9.000000pt; font-family: ’TimesNewRomanPSMT’;">While eye gaze data contain promising clues for inferring the interests of viewers of digital catalog content, viewers often dynamically switch their focus of attention. As a result, a direct application of conventional behavior analysis techniques, such as topic models, tends to be affected by items or attributes of little or no interest to the viewer. To overcome</span><span style="font-size: 9.000000pt; font-family: ’TimesNewRomanPSMT’;"> this limitation, we need to identify “when” the user compares items and to detect “which attribute types/values” reflect the user’s interest. This paper proposes a novel two-step</span><span style="font-size: 9.000000pt; font-family: ’TimesNewRomanPSMT’;"> approach to addressing these needs. Specifically, we introduce a likelihood-based short-term analysis method as the first step of the approach to simultaneously determine comparison phases of browsing and detect the attributes on which the viewer focuses, even when the attributes cannot be directly obtained from gaze points. Using probabilistic latent semantic analysis, we show that this short-term analysis step greatly improves the results of the subsequent step. The effectiveness of the framework is demonstrated in terms of the ca</span><span style="font-size: 9.000000pt; font-family: ’TimesNewRomanPSMT’;">pability to extract combinations of attributes relevant to the viewer’s interest, which we </span><span style="font-size: 9.000000pt; font-family: ’TimesNewRomanPSMT’;">call </span><span style="font-size: 9.000000pt; font-family: ’TimesNewRomanPS’; font-style: italic;">aspects</span><span style="font-size: 9.000000pt; font-family: ’TimesNewRomanPSMT’;">, and also to estimate the interest described by these aspects. </span></p> </div> </div> </div> </div>}, number={1}, journal={Journal of Eye Movement Research}, author={Shimonishi, Kei and Kawashima, Hiroaki}, year={2020}, month={Apr.} }