activity
20162026
most citedConfidence Interval of Probability Estimator of Laplace Smoothing

21 citations · 54 across the 16 of their papers we have counts for

collaborators

25 papers

cs.SI2026

Mapping Social Media User Behaviors in Reciprocity Space

Shiori Hironaka, Hayato Oshimo, Mitsuo Yoshida +1

Social media users exhibit diverse behavioral patterns as platforms function simultaneously as information and friendship networks. We introduce a reciprocity-based framework mappi…

cs.HC2023★ 8 cited

Large Language Model-based System to Provide Immediate Feedback to Students in Flipped Classroom Preparation Learning

Shintaro Uchiyama, Kyoji Umemura, Yusuke Morita

This paper proposes a system that uses large language models to provide immediate feedback to students in flipped classroom preparation learning. This study aimed to solve challeng…

cs.DS2022

Comparing Two Counting Methods for Estimating the Probabilities of Strings

Ayaka Takamoto, Mitsuo Yoshida, Kyoji Umemura

There are two methods for counting the number of occurrences of a string in another large string. One is to count the number of places where the string is found. The other is to de…

cs.SI2022★ 3 cited

Follower--Followee Ratio Category and User Vector for Analyzing Following Behavior

Hayato Oshimo, Shiori Hironaka, Mitsuo Yoshida +1

Analyzing following behavior is important in many applications. Following behavior may depend on the main intention of the follower. Users may either follow their friends or they m…

cs.CL2021

Feature Selective Likelihood Ratio Estimator for Low- and Zero-frequency N-grams

Masato Kikuchi, Mitsuo Yoshida, Kyoji Umemura +1

In natural language processing (NLP), the likelihood ratios (LRs) of N-grams are often estimated from the frequency information. However, a corpus contains only a fraction of the p…

cs.SI2021

Comparison of Indicators of Location Homophily Using Twitter Follow Graph

Shiori Hironaka, Mitsuo Yoshida, Kyoji Umemura

Location homophily is a tendency of Twitter users whose followers tend to be in the same or nearby areas. Intuitively, although users with a higher number of follower relationships…