Goal: Build a question answering system using Wikidata that answers factoid questions.
Goal: build a smart office/classroom. The system accesses the user’s profile via face recognition and tunes the connected devices in the room/office according to the preferences in the profile. As a first iteration, could just be face recognition + reporting on the status of the devices, room temperature, weather and traffic conditions based on the user’s location.
Goal: Build a personal knowledge graph for a fictional character and “grow” the graph with the character over time. “What present did I get from my brother for my 15th birthday?” etc. Fictional person is 60 years old and interacts with the personal graph s/he created at age 15. Alzheimer’s, memory issues, therapy sessions, password hints, etc.
Goal: Build a system that generates a knowledge graph from photos and videos.
Goal: Build a hybrid system to represent the meaning of jokes in terms of a knowledgegraph as well as embeddings towards analysis and generation of humor.
Create an ontology including non-language visual recognition properties to assess threat posed in situations where guns are visually identified automatically.
This is a multi-lingual multidisciplinary project on the semantics of the lexical field LAUGH (laugh, smile, grin, etc.), including semantics, literature, computational linguistics, translation studies, phonology, and humor research. The project compares the translations of lemmata in the field in a growing number of languages to analyze the semantics of the field.
This project is creating a medical ontology and the methods and tools to evaluate it against existing medical knowledge bases. The intended application is a personal health information system (PHIS) for Alzheimer’s patients and their caregivers.
This project is creating an online corpus of J.R.R. Tolkien’s major works, including The Hobbit and Lord of the Rings, in a transformative fashion by annotating and and presenting the texts to analyze their stylistics and semantics.