Search Results for author: Eiji Aramaki

Found 23 papers, 3 papers with code

Mitigation of Diachronic Bias in Fake News Detection Dataset

no code implementations28 Aug 2021 Taichi Murayama, Shoko Wakamiya, Eiji Aramaki

Fake news causes significant damage to society. To deal with these fake news, several studies on building detection models and arranging datasets have been conducted.

Fake News Detection

Single Model for Influenza Forecasting of Multiple Countries by Multi-task Learning

no code implementations5 Jul 2021 Taichi Murayama, Shoko Wakamiya, Eiji Aramaki

The accurate forecasting of infectious epidemic diseases such as influenza is a crucial task undertaken by medical institutions.

Multi-Task Learning

Biomedical Entity Linking with Contrastive Context Matching

1 code implementation14 Jun 2021 Shogo Ujiie, Hayate Iso, Eiji Aramaki

We introduce BioCoM, a contrastive learning framework for biomedical entity linking that uses only two resources: a small-sized dictionary and a large number of raw biomedical articles.

Contrastive Learning Entity Linking

End-to-end Biomedical Entity Linking with Span-based Dictionary Matching

no code implementations21 Apr 2021 Shogo Ujiie, Hayate Iso, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki

Disease name recognition and normalization, which is generally called biomedical entity linking, is a fundamental process in biomedical text mining.

Entity Linking

KART: Privacy Leakage Framework of Language Models Pre-trained with Clinical Records

no code implementations31 Dec 2020 Yuta Nakamura, Shouhei Hanaoka, Yukihiro Nomura, Naoto Hayashi, Osamu Abe, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki

Since the concept of the KART framework is domain agnostic, it can contribute to the establishment of privacy guidelines of language models beyond the biomedical domain.

Offensive Language Detection on Video Live Streaming Chat

no code implementations COLING 2020 Zhiwei Gao, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki

To make use of the similarity in offensive expressions among different social media platforms, we adopted state-of-the-art models trained on offensive expressions from Twitter for our Twitch data (i. e., transfer learning).

Transfer Learning

NAIST COVID: Multilingual COVID-19 Twitter and Weibo Dataset

1 code implementation17 Apr 2020 Zhiwei Gao, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki

This has affected the social life of people owing to enforcements, such as "social distancing" and "stay at home."

Multivariate Linear Regression of Symptoms-related Tweets for Infectious Gastroenteritis Scale Estimation

no code implementations WS 2017 Ryo Takeuchi, Hayate Iso, Kaoru Ito, Shoko Wakamiya, Eiji Aramaki

Based on these results, we can infer that social sensors can reliably detect unseasonal and local disease events under certain conditions, just as they can for seasonal or global events.

Event Detection

Density Estimation for Geolocation via Convolutional Mixture Density Network

no code implementations8 May 2017 Hayate Iso, Shoko Wakamiya, Eiji Aramaki

Nowadays, geographic information related to Twitter is crucially important for fine-grained applications.

Density Estimation

Forecasting Word Model: Twitter-based Influenza Surveillance and Prediction

no code implementations COLING 2016 Hayate Iso, Shoko Wakamiya, Eiji Aramaki

Because of the increasing popularity of social media, much information has been shared on the internet, enabling social media users to understand various real world events.

Future prediction

MedNLPDoc: Japanese Shared Task for Clinical NLP

no code implementations WS 2016 Eiji Aramaki, Yoshinobu Kano, Tomoko Ohkuma, Mizuki Morita

Due to the recent replacements of physical documents with electronic medical records (EMR), the importance of information processing in medical fields has been increased.

Information Retrieval

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