Intervention-Based Clustering

Title: Intervention-Based Clustering Dates: 2016 – 2020 Researchers: Igor Kulev and Pearl Pu Keywords: activities of daily living, machine learning, timeseries analysis, clustering Abstract: While an increase in physical activity levels has been shown to be the most effective and important intervention strategy to improve health in elderly populations, it is notoriously difficult to increase […]

Chatbot

We present a chatbot that generates responses to people’s queries. The model is trained using 35,429 pair of conversations from the Big Bang Theory. Run this demo.

Dictionaries

Title: Dictionaries Contributors: Onur Yürüten and Pearl Pu Keywords: food, mood, emotion recognition, GALC in Chinese, emojis, social media analysis, twitter, hashtag Description: Here we provide downloads for a dictionary of food words, the GALC in Chinese, a collection of emojis that have been mapped to the Geneva Emotion Wheel. Links: Main Page

Curated Datasets for Food and Mood-Related Tweets

Title: Food and Mood-Related Tweets Contributors: Onur Yürüten and Pearl Pu Keywords: food, mood, emotion recognition, social media analysis, twitter, hashtag, emojis Description: In the course of our research for understanding the relations between food and mood, we curated several datasets of social media posts. Links: Main Page

Geneva Emotion Wheel-based Emotion Lexicons and Data

Title: GEW-based Emotion Lexicons Contributors: Valentina Sintsova and Pearl Pu Keywords: emotion recognition, social media analysis, distant supervision, twitter, OlympLex, GALC-R, PMI-hash, Dystemo, EMO-hash, SREC, sports related emotion corpus Description: In the course of our research for advancing emotion recognition in tweets, we produced several emotion lexicons, collected emotional data, and annotated some data with […]

Curated Datasets of Activities of Daily Living

Title: Curated Datasets of ADL Contributors: Onur Yürüten and Pearl Pu Keywords: Activities of daily living, activity recognition, data mining, timeseries analysis, statistical analysis, behavior recommenders Description: In the course of our research for advancing recommender systems for healthy lifestyles, we curated or obtained several datasets concerning activities of daily living, including physical activity and […]

Behavior Recommender Systems

Title: Behavior Recommender Systems Dates: 2013-2017 Researchers: Onur Yuruten and Pearl Pu Keywords: Activities of daily living, activity recognition, data mining, time series analysis, statistical analysis, behavior recommenders Abstract: Sedentary lifestyles influence the onset of many serious health problems. Healthy behavior change is an arduous task, but behavior recommenders can help their users achieve it. This novel […]