Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- 2020 US Cyber Challenge National Championship (1)
- Alina Kuzmenkova (1)
- Animation Jam (1)
- Artificial intelligence (1)
- Black maternal health (1)
-
- CHA +DePaul Youth Partnership (1)
- COVID-19 (1)
- Cole Anderson (1)
- Computational linguistics (1)
- Data labeling (1)
- DePaul Center for Data Science (1)
- DePaul Experimental Film Showcase (1)
- DePaul School of Design (1)
- DePaul School of Nursing (1)
- DeSports (1)
- Digital Youth Divas (1)
- Entity recognition (1)
- Entity relations (1)
- Equity and Health Innovations (EHI) Design Research Lab (1)
- Hollywood Reporter (1)
- Idea Realization Lab (1)
- Illinois PPE Network (1)
- Machine learning (1)
- Material Sciences (1)
- Natural Language Processing (1)
- PixelPop Festival (1)
- Polymer Materials (1)
- STEM (1)
- School of Cinematic Arts (1)
- Storytelling (1)
- Publication Type
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Ensemble Labeling Towards Scientific Information Extraction (Elsie), Erin Murphy
Ensemble Labeling Towards Scientific Information Extraction (Elsie), Erin Murphy
College of Computing and Digital Media Dissertations
Extracting scientific facts from unstructured text is difficult due to challenges specific to the ambiguity of the language, the complexity of the scientific named entities and relations to be extracted. This problem is well illustrated through the extraction of polymer names and their properties. Even in the cases where the property is a temperature, identifying the polymer name associated with the temperature may require expertise due to the use of acronyms, synonyms, complicated naming conventions and by the fact that new polymer names are being “introduced” to the vernacular as polymer science advances. While there exist domain-specific machine learning toolkits …
Fall 2020
In The Loop
Studio CDM Documents Remote Initiatives; "Tom of Your Life" Film Release; Animation Jam Goes Virtual; DePaul Experimental Film Showcase 2020; Trackmania Soundtrack; Alumni Games at Pixel Pop; Alumnus Commemorates St. Vincent de Paul; Cybersecurity Champion Alina Kuzmenkova; Walking the Walk: Youth programs at CDM express DePaul’s Vincentian values; Fair Treatment: Three initiatives address racial inequity in health care; They've Got You Covered: A School of Design instructor leads a cottage industry of makers protecting essential workers from the novel coronavirus; Meet Would-Be Hot Topic Influencer Vera Drew; Data Detectives: CDM helps Chicago track the racial proportions of its COVID-19 cases
Pathways To The Native Storyteller: A Method To Enable Computational Story Understanding, Aramide O. Kehinde
Pathways To The Native Storyteller: A Method To Enable Computational Story Understanding, Aramide O. Kehinde
College of Computing and Digital Media Dissertations
The primary objective of this thesis is to develop a method that uses machine learning algorithms to enable computational story understanding. This research is conducted with the aim of establishing a system called the Native Storyteller that plans and creates storytelling experiences for human users. The paper first establishes the desired capabilities of the system and then deep dives into how to enable story understanding, which is the core ability the system needs to function. As such, the research places emphasis on natural language processing and its application to solving key problems in this context. Namely, machine representation of story …