- 1 OurMovieSimilarity: Cognitive Similarity-based Recommendation
- 2 BIBIDA: Big Bibliography Data Analytics
- 3 Dakgalbi: Scalable Recommendation Framework based on Information Fusion
- 4 From Internet of Things to Internet of Agents
- 5 SocioScope: a Framework for Capturing Internet of Social Knowledge
- 6 Story Engineering: from Quantizing to Understanding Stories
- 7 Social RecSys
OurMovieSimilarity: Cognitive Similarity-based Recommendation
- How to measure the cognitive similarity between users?
BIBIDA: Big Bibliography Data Analytics
Dakgalbi: Scalable Recommendation Framework based on Information Fusion
- Data is represented as a matrix. There have many kinds of matrix based on the types of data. DakGalBi system is able to process the matrix by incremental consolidation. The more data it has received, the more accurate it produces the predictions.
From Internet of Things to Internet of Agents
With the developing of Internet of Things (IoT), a new concept is introduced, which is named Internet of Agent (IoA), this concept enables connected agent into smart agent which includes three conceptual standpoints: Identification, Communication and Interaction. Our research focuses on the interaction of smart agents in terms of computational negotiation which is able to apply various domains such as smart transportation, smart home and so on.
SocioScope: a Framework for Capturing Internet of Social Knowledge
Social data is one of important material for representing social activities. However, efficiently collecting social data from multiple sources is extremely hard due its big-data attributes. Moreover, discovering hidden patterns between social data to understand our society is actually a big challenge. Especially, knowledge around us is not stable but dynamically change over time, therefore, we need to refresh it promptly. SocioScope is created as an automatically tool to overcome aforementioned problems. In addition, other researchers can utilize SocioScope as a framework for reducing their effort time with essential tasks (i.e., collecting data, pre-processing data, and analyzing data).
Story Engineering: from Quantizing to Understanding Stories
"Narratives structure our understanding of the world and ourselves." 
- PI: Jason J. Jung
- Participants: O-Joun Lee, Luong Vuong Nguyen, and Nayoung Jo
This research project aims to model and analyze stories of the narrative work (i.e., artworks that contain stories) computationally. Our previous studies on this area are mainly based on the character network (i.e., social networks between characters that appear in the narrative work).
Student’s Involvement and Expected Outcomes:
- Proposing a novel approach for modeling and analyzing stories.
- Developing an application which utilizes the character network.
- Developing and refactoring 'Character Network Builder' with multiple data sources (e.g., the script, video, and audio of movies).
- Collecting data for experiments from real narrative works in various media, genres, and formats.
- Luong Vuong Nguyen: Movie Similarity Collector, 
- O-Joun Lee: Story2Vec, [github repository]
- Nayoung Jo: Character Network Extractor, [github repository]
- O-Joun Lee, Nayoung Jo, Jason J. Jung: Measuring Character-based Story Similarity by Analyzing Movie Scripts. The 1st Workshop on Narrative Extraction From Text (Text2Story 2018), co-located with the 40th European Conference on Information Retrieval (ECIR 2018), Grenoble, France; 03/2018
- O-Joun Lee, Jason J. Jung: Explainable Movie Recommendation Systems by using Story-based Similarity. The workshop on Explainable Smart Systems (ExSS 2018), held in conjunction with the 23rd International Conference on Intelligent User Interfaces (IUI 2018), Tokyo, Japan; 03/2018
- O-Joun Lee, Jason J. Jung: Modeling affective character network for story analytics. Future Generation Computer Systems; DOI:10.1016/j.future.2018.01.030 (To appear)
- Tran, Quang Dieu, Dosam Hwang, and Jason J. Jung. "Character-based indexing and browsing with movie ontology." Journal of Intelligent & Fuzzy Systems 32.2 (2017): 1229-1240.
- Quang Dieu Tran, Dosam Hwang, O-Joun Lee, Jai E. Jung: Exploiting Character Networks for Movie Summarization. Multimedia Tools and Applications 04/2017; 76(8):10357–10369., DOI:10.1007/s11042-016-3633-6
- Jai E. Jung†, O-Joun Lee†‡, Eun-Soon You†, Myoung-Hee Nam†: A Computational Model of Transmedia Ecosystem for Story-based Contents. Multimedia Tools and Applications 04/2017; 16(8):10371–10388., DOI:10.1007/s11042-016-3626-5 († Co-first Authors, ‡ Corresponding Author)
- Quang Dieu Tran, Dosam Hwang, O.-Joun Lee, Jason J. Jung: A Novel Method for Extracting Dynamic Character Network from Movie. Big Data Technologies and Applications, Edited by Jason J. Jung, Pankoo Kim, 06/2017: pages 48-53; Springer International Publishing., ISBN: 978-3-319-58967-1, DOI:10.1007/978-3-319-58967-1_6
- Myeong-Yeon Yi, O-Joun Lee, Jason J. Jung: MBTI-based Collaborative Recommendation System: A Case Study of Webtoon Contents. Context-Aware Systems and Applications, Edited by Cong Vinh Phan, Alagar Vangalur, 04/2016: pages 101-110; Springer International Publishing., ISBN: 978-3-319-29236-6, DOI:10.1007/978-3-319-29236-6_11
- Tran, Quang Dieu, Dosam Hwang, and Jason J. Jung. "Movie summarization using characters network analysis." Computational Collective Intelligence. Springer, Cham, 2015. 390-399.
- Tran, Quang Dieu, and Jai E. Jung. "CoCharNet: Extracting Social Networks using Character Co-occurrence in Movies." J. UCS 21.6 (2015): 796-815.
- Jason J. Jung, Eunsoon You, and Seung-Bo Park. "Emotion-based character clustering for managing story-based contents: a cinemetric analysis." Multimedia tools and applications 65.1 (2013): 29-45.
- Seung-Bo Park, Eunsoon You, and Jason J. Jung. "Potential emotion word in movie dialog." in Proceedings of the International Conference on IT Convergence and Security 2011. Springer, Dordrecht, 2012.
This application is personal diary about movie watching history, and you can see many information about the movies, analyzed your history using PC and Mobile.
MyMovieHistory MyMovieHistory WEBSITE