Multimedia Computing Group
The Multimedia Computing (MMC) Group develops algorithms for enriching, accessing, and searching large quantities of data. Such algorithms lie at the core of tomorrows’ search engines and large-scale recommender systems. The group sets its focus on developing systems that are oriented to the needs of users, and that solve the challenges faced by large-scale online content and service providers. Multimedia data analytics also has applications in the full range of fields that benefit from data science, including health, telecom, and geosciences.
The group has a track record of developing technologies that make possible optimized interaction with large collections of multimedia data (e.g., images, video, and music) in real-world contexts (e.g., within social networks). Our work requires a combination of mathematical models, machine learning techniques, and practical skills in algorithm development and evaluation. The members of the MMC group share expertise in multimedia information retrieval, recommender systems, multimedia signal processing, social network analysis, human computation (crowdsourcing) and quality of experience. Collaborations include joint work with researchers from Yahoo Labs, Telefónica Research, Microsoft Research and Google.
The work being carried out in the MMC Group encompasses a broad palette of research directions including:
- Multimedia content analysis and search
- Semantics extraction from multimedia data
- Multi-modal query expansion
- Multi-source search result reranking
- Multimedia information retrieval in a social network context
- Modeling information propagation and relationships in social networks
- Collaborative recommender systems
- Social recommendation
- Interaction with multimedia content
- (Affective) User profiling
- User (search/uploader) intent
- Query failure prediction
- Quality of multimedia experience
- Multimedia content management
- Multimedia databases and dataspaces
- Entity retrieval
15 september 2019
Best paper award for Jaeyoung Choi
Jaeyoung Choi PhD –student in INSY’s MMC group/ICSI, California, won best paper award at the IEEE 5th International Conference on Multimedia Big Data (Singapore).
12 september 2019
Forecasting Time Series with VARMA Recursions on Graphs
Recent development in signal processing and network science has brought new tools for processing time series. However, it was not yet clear on how to exploit the structure of a network for predicting the evolution of time series.
18 juli 2019
Huijuan Wang, Co-founder and Chair of Dutch Network Science Society, Board member of the international Network Science Society
Huijuan Wang and Linda Douw (Amsterdam UMC) have founded the Dutch Network Science Society http://www.netsci.nl, which kicked off with a national symposium http://www.netsci.nl/node/4 on 7th May 2019 at TUDelft. Dutch Network Science Society is the Dutch Chapter of the international Network Science Society https://netscisociety.net/
18 juli 2019
Huijuan Wang is on the Editorial Board of Nature’s Scientific Report.
More about the journal Scientific Report by Nature can be found here https://www.nature.com/srep/