A two-step approach for interest estimation from gaze behavior in digital catalog browsing
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 item...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Journal of Eye Movement Research |
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| Online Access: | https://bop.unibe.ch/JEMR/article/view/5868 |
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| author | Kei Shimonishi Hiroaki Kawashima |
| author_facet | Kei Shimonishi Hiroaki Kawashima |
| author_sort | Kei Shimonishi |
| collection | DOAJ |
| description | 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 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 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 capability to extract combinations of attributes relevant to the viewer’s interest, which we call aspects, and also to estimate the interest described by these aspects. |
| format | Article |
| id | doaj-art-ddfe3b33fe56468ea77b33dc38f6fb21 |
| institution | DOAJ |
| issn | 1995-8692 |
| language | English |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Eye Movement Research |
| spelling | doaj-art-ddfe3b33fe56468ea77b33dc38f6fb212025-08-20T03:04:08ZengMDPI AGJournal of Eye Movement Research1995-86922020-04-0113110.16910/jemr.13.1.4A two-step approach for interest estimation from gaze behavior in digital catalog browsingKei Shimonishi0Hiroaki Kawashima1Kyoto UniversityUniversity of HyogoWhile 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 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 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 capability to extract combinations of attributes relevant to the viewer’s interest, which we call aspects, and also to estimate the interest described by these aspects.https://bop.unibe.ch/JEMR/article/view/5868decision makingeye movementaspect-modelregion of interestgazeattention |
| spellingShingle | Kei Shimonishi Hiroaki Kawashima A two-step approach for interest estimation from gaze behavior in digital catalog browsing Journal of Eye Movement Research decision making eye movement aspect-model region of interest gaze attention |
| title | A two-step approach for interest estimation from gaze behavior in digital catalog browsing |
| title_full | A two-step approach for interest estimation from gaze behavior in digital catalog browsing |
| title_fullStr | A two-step approach for interest estimation from gaze behavior in digital catalog browsing |
| title_full_unstemmed | A two-step approach for interest estimation from gaze behavior in digital catalog browsing |
| title_short | A two-step approach for interest estimation from gaze behavior in digital catalog browsing |
| title_sort | two step approach for interest estimation from gaze behavior in digital catalog browsing |
| topic | decision making eye movement aspect-model region of interest gaze attention |
| url | https://bop.unibe.ch/JEMR/article/view/5868 |
| work_keys_str_mv | AT keishimonishi atwostepapproachforinterestestimationfromgazebehaviorindigitalcatalogbrowsing AT hiroakikawashima atwostepapproachforinterestestimationfromgazebehaviorindigitalcatalogbrowsing AT keishimonishi twostepapproachforinterestestimationfromgazebehaviorindigitalcatalogbrowsing AT hiroakikawashima twostepapproachforinterestestimationfromgazebehaviorindigitalcatalogbrowsing |