Ayae Ide

I am a PhD candidate in informatics at Pennsylvania State University’s College of Information Sciences and Technology. I am fortunate to be advised by Dr.Tanusree Sharma. My current research interests are usable security and privacy for Web3/Decentralized Internet.

Platform Transparency: With my industry experience, I’ve observed significant challenges in the transparency of data-sharing practices. I am passionate about designing transparent interfaces that foster trust and accountability for building fair and ethical online platforms.

Decentralized Internet: My interest in decentralized systems arises from a desire to explore structures that empower users and reduce platform dominance. These systems align with my broader goal of promoting user autonomy by minimizing the influence of centralized entities.

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.