scholarly journals A two-step approach for interest estimation from gaze behavior in digital catalog browsing

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Kei Shimonishi ◽  
Hiroaki Kawashima
Keyword(s):  
Semantic Analysis ◽  
Eye Gaze ◽  
Probabilistic Latent Semantic Analysis ◽  
Analysis Method ◽  
Gaze Behavior ◽  
Short Term ◽  
Analysis Techniques ◽  
Subsequent Step ◽  
Conventional Behavior ◽  
Term Analysis

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.

scholarly journals Finding author similarity by clustering probabilistic LSA factors in INDIAN english authors poetry

2018 ◽  
Vol 7 (2.7) ◽  
pp. 1096
Author(s):  
K Praveen kumar ◽  
Venkata Naresh Mandhala ◽  
Sudheshna Vempati ◽  
Dr Subba Rao Peram
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Probabilistic Methods ◽  
Distance Measures ◽  
High Dimensionality ◽  
Probabilistic Latent Semantic Analysis ◽  
Analysis Method ◽  
Indian English ◽  
Clear Distance ◽  
Learning Data

High dimensionality and sparseness is the big challenge to the data scientists to discover the similarity among the documents. In unsuper-vised learning data is unlabeled and there is no clear distance measures to discover the clusters among the data. In this paper we considered Indian English Authors poems to cluster them using Probabilistic Latent Semantic Analysis, using which we analyzed the authors similarity. We compared the results of clustering with Latent Semantic Analysis method, a word occurrence method. In this case, Results are shown that probabilistic methods are performing good clustering than the word occurrence method.  

scholarly journals Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 112 ◽  
Author(s):  
Andrzej Przybylak ◽  
Radosław Kozłowski ◽  
Ewa Osuch ◽  
Andrzej Osuch ◽  
Piotr Rybacki ◽  
...  
Keyword(s):  
Image Analysis ◽  
Neural Model ◽  
Assessment Method ◽  
Analysis Method ◽  
Potato Tubers ◽  
Specialized Knowledge ◽  
Analysis Techniques ◽  
Quality Assessment Method ◽  
Sorting Process ◽  
Image Analysis Techniques

This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

scholarly journals Eye gaze differences in school scenes between preschool children and adolescents with high-functioning autism spectrum disorder and those with typical development

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Yuko Ishizaki ◽  
Takahiro Higuchi ◽  
Yoshitoki Yanagimoto ◽  
Hodaka Kobayashi ◽  
Atsushi Noritake ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Preschool Children ◽  
Children And Adolescents ◽  
Eye Gaze ◽  
Autism Spectrum ◽  
Typical Development ◽  
Human Face ◽  
Gaze Behavior ◽  
Psychosomatic Symptoms ◽  
Children With Asd

Abstract Background Children with autism spectrum disorder (ASD) may experience difficulty adapting to daily life in a preschool or school settings and are likely to develop psychosomatic symptoms. For a better understanding of the difficulties experienced daily by preschool children and adolescents with ASD, this study investigated differences in eye gaze behavior in the classroom environment between children with ASD and those with typical development (TD). Methods The study evaluated 30 children with ASD and 49 children with TD. Participants were presented with images of a human face and a classroom scene. While they gazed at specific regions of visual stimuli, eye tracking with an iView X system was used to evaluate and compare the duration of gaze time between the two groups. Results Compared with preschool children with TD, preschool children with ASD spent less time gazing at the eyes of the human face and the object at which the teacher pointed in the classroom image. Preschool children with TD who had no classroom experience tended to look at the object the teacher pointed at in the classroom image. Conclusion Children with ASD did not look at the human eyes in the facial image or the object pointed at in the classroom image, which may indicate their inability to analyze situations, understand instruction in a classroom, or act appropriately in a group. This suggests that this gaze behavior of children with ASD causes social maladaptation and psychosomatic symptoms. A therapeutic approach that focuses on joint attention is desirable for improving the ability of children with ASD to adapt to their social environment.

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