Ayae Ide

I am a PhD student in informatics with a primary focus on understanding privacy perceptions and designing user-centered privacy interfaces.

Privacy Communications and User Interfaces: I explore how these factors influence user decisions related to data sharing on online platforms. I aim to provide users with better-informed choices to respect user privacy and maximize the data power of products, particularly in the context of evolving data-centric systems and privacy regulations.

news

Jun 22, 2023	Published a blog post 🙌

selected publications

2018

AAAI Symposia

Policy Decision Support System in Aging Society Based on Probabilistic Latent Spatial Semantic Structure Modeling

Ayae Ide, Yoichi Motomura, and Takao Terano

Technical Reports of 2018 AAAI Spring Symposium Series, 2018

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This paper analyzes a questionnaire survey data on elderly people in order to investigate regional characteristics of their living activities. For the purpose, we use Probabilistic Latent Spatial Semantic (PLSS) Modeling, which is integrated the two methods: probabilistic latent semantic analysis (pLSA) and Bayesian network (BN). First, we aggregate each individual’s survey record by postal code; Second, we find characteristics of the region by pLSA; Third, we use BN to clarify factors of this regional disparity. From the study, we are able to identify critical information to support decisions for a manager in a local government: i) There is regional disparity in terms of social network; and ii) The regional disparity of social network will improve by neighborhood facilities. Such information will be of use for designing the super-aged society in the near future. We propose policy decision support system in aging society based on PLSS Modeling.

2017

IEEE Big Data

Analyzing regional characteristics of living activities of elderly people from large survey data with probabilistic latent spatial semantic structure modeling

Ayae Ide, Kazuya Yamashita, Yoichi Motomura, and Takao Terano

Proceedings of 2017 IEEE International Conference on Big Data, 2017

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This paper analyzes a questionnaire survey data on elderly people in order to investigate regional characteristics of their living activities. For the purpose, we use Probabilistic Latent Spatial Semantic (PLSS) Modeling, which is integrated the two methods: probabilistic latent semantic analysis (pLSA) and Bayesian network (BN). First, we aggregate each individual’s survey record by postal code; Second, we find characteristics of the region by pLSA; Third, we use BN to clarify factors of this regional disparity. From the study, we are able to identify critical information to support decisions for a manager in a local government: i) The responses of the elderly are correlated with their resident areas; and ii) The regional disparity of social network will improve by neighborhood facilities. Such information will be of use for designing the super-aged society in the near future.