【採択】修士1年生浜中君の研究が国際会議ACM HotMobile 2023 poster sessionにacceptされました – ‘ Estimation of user personality traits on the Web Using Multi-Task Learning’

Abstract:

We focus on user’s personality traits and propose a method to estimate user’s personality traits from footprint logs collected from news platform services and search queries, with the aim of constructing a news recommendation system using the personality traits. We constructed supervised machine learning models for 8871 users, using the features calculated from news browsing logs as explanatory variables and personality traits (Big Five) collected via a questionnaire using crowdsourcing as objective variables. Five estimators were constructed for each Big Five traits, and the results of comparative evaluation using multiple algorithms showed that the accuracy of AUC 0.634 was obtained for the agreeableness trait.