Information till medarbetare med anledning av covid-19 (Uppdaterad: 21 oktober 2020)

Hoppa direkt till innehållet

Database and Data Mining

The research interests of DDM group include data federation and privacy preservation by applying techniques of text mining, natural language processing, machine learning, and semantic web.

The research group of Deep Data Mining was established to develop algorithms and implement prototype for multi-sources heterogeneous information federation and privacy preservation on multimodal data.

Regarding datatypes to integrate, we consider data from structured (e.g, records in DB), semi-structured (e.g, XML, JSON) and unstructured sources (e.g, news, social media). In a broad view of the core techniques, our group applies technologies of database, data mining, natural language processing, machine learning, and ontology based semantic web technology. As application-driven research, we aim to realize general data integration framework to adapt multiple applications (e.g, information retrieval, recommendation systems, online advertisements) and meanwhile acquire the unique characteristics of domain-data to boost the integration accuracy on specialized domains (e.g, social networks, demographic, review data).


Publikationer Database and Mining

ECIR 2020: Advances in Information Retrieval, Springer 2020 : 443-448
Ait-Mlouk, Addi; Jiang, Lili
IEEE Access, IEEE 2020, Vol. 8 : 149220-149230
Ait-Mlouk, Addi; Jiang, Lili
Proceedings of the 28th ACM International Conference on Multimedia (MM ’20), ACM Digital Library 2020 : 1-9
Vu, Xuan-Son; Le, Duc-Trong; Edlund, Christoffer; et al.
Proceedings of the 20th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), 2019
Vu, Xuan-Son; Santra, Abhishek; Chakravarthy, Sharma; et al.
IEEE/ACM Transactions on Computational Biology & Bioinformatics, IEEE 2019, Vol. 16, (3) : 980-993
Wang, Aiguo; Chen, Ye; An, Ning; et al.
Proceedings of The World Wide Web Conference WWW 2019, New York, NY, USA: ACM Digital Library 2019 : 3595-3599
Vu, Xuan-Son; Ait-Mlouk, Addi; Elmroth, Erik; et al.
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), Incoma Ltd. 2019 : 1285-1294
Vu, Xuan-Son; Vu, Thanh; Tran, Son N.; et al.
Proceedings of the 20th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), 2019
Vu, Xuan-Son; Tran, Son N.; Jiang, Lili
Proceedings of the 9th Global WordNet Conference (GWC 2018), Singapore: Nanyang Technological University (NTU) 2018 : 173-182
Vu, Xuan-Son; Flekova, Lucie; Jiang, Lili; et al.
Proceedings of the 19th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), 2018
Vu, Xuan-Son; Jiang, Lili
TMA Conference 2017: Proceedings of the 1st Network Traffic Measurement and Analysis Conference
Gonzalez, Roberto; Jiang, Lili; Ahmed, Mohamed; et al.
K-CAP 2017: Proceedings of the Knowledge Capture Conference
Vu, Xuan-Son; Jiang, Lili; Brändström, Anders; et al.
Computers in Biology and Medicine, Elsevier 2016, Vol. 77 : 76-89
Chen, Ye; Wang, Aiguo; Ding, Huitong; et al.
Vu, Xuan-Son; Nguyen, Thanh-Son; Le, Duc-Trong; et al.

Nyheter Datavetenskap

Virginia Dignum ny medlem i Global Partnership on AI
Publicerad: 25 okt, 2020

Professor Virginia Dignum ny medlem i internationell grupp för AI.

Topplistade AI-bolag bygger på forskning vid Umeå universitet
Publicerad: 21 okt, 2020

Algoryx, Infobaleen, Prediktera och Shimmercat hyllas på svenska AI-kartan.

Datorbaserad designoptimering och ljudutbredning i blåst
Publicerad: 19 okt, 2020

Linus introducerar ett ramverk för filter vid datorbaserad designoptimering och analyserar modeller för ljud.

Integritet: ett viktigt begrepp i vår tid
Publicerad: 15 okt, 2020

Xuan-Son Vu behandlar behovet av integritetsgaranti och analys i maskininlärning med stora datamängder.

Forskning kan ge mindre isbildning i arktiskt klimat
Publicerad: 09 okt, 2020

Forskare ska bidra till mer kunskap om isbildning i arktiska regioner.