An Inference-Based Framework to Manage Data Provenance in Geoscience Applications

Autor: Andreas Wombacher, Peter M. G. Apers, Mohammad Rezwanul Huq

Publikováno v: IEEE transactions on geoscience and remote sensing, 51(11), 5113-5130. IEEE

Data provenance allows scientists to validate their model as well as to investigate the origin of an unexpected value. Furthermore, it can be used as a replication recipe for output data products. However, capturing provenance requires enormous effor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f34149c6db46c6bc7bf3ed7c721b7375
https://doi.org/10.1109/tgrs.2013.2247769

A context-aware preference model for database querying in an Ambient Intelligent environment

Autor: Ling Feng, Peter M. G. Apers, Arthur H. van Bunningen

Publikováno v: Lecture Notes in Computer Science ISBN: 9783540378716
DEXA
Proceedings of the 17th International Conference on Database and Expert Systems Applications (DEXA 2006), 33-43
STARTPAGE=33;ENDPAGE=43;TITLE=Proceedings of the 17th International Conference on Database and Expert Systems Applications (DEXA 2006)

Users' preferences have traditionally been exploited in query personalization to better serve their information needs. With the emerging ubiquitous computing technologies, users will be situated in an Ambient Intelligent (AmI) environment, where user

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff9990fc87ae132407de35346949fb91
https://doi.org/10.1007/11827405_4

Distributed Global Transaction Support for Workflow Management Applications

Autor: Paul Grefen, Jochem Vonk, E.M. Boertjes, Peter M. G. Apers

Publikováno v: Lecture Notes in Computer Science ISBN: 9783540664482
DEXA
Distributed Global Transaction Support for Workflow Management Applications (DEXA 1999), 942-951
STARTPAGE=942;ENDPAGE=951;TITLE=Distributed Global Transaction Support for Workflow Management Applications (DEXA 1999)

Workflow management systems require advanced transaction support to cope with their inherently long-running processes. The recent trend to distribute workflow executions requires an even more advanced transaction support system that is able to handle

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5146b7591aa22122ab527445575d72c4
https://doi.org/10.1007/3-540-48309-8_89

Empirical Co-occurrence Rate Networks for Sequence Labeling

Autor: Zhemin Zhu, Andreas Wombacher, Djoerd Hiemstra, Peter M. G. Apers

Publikováno v: ICMLA (1)
Dutch-Belgian Database Day, DBDBD 2013
Proceedings of the 12th International Conference on Machine Learning and Applications, ICMLA 2013, 93-98
STARTPAGE=93;ENDPAGE=98;TITLE=Proceedings of the 12th International Conference on Machine Learning and Applications, ICMLA 2013

Sequence labeling has wide applications in many areas. For example, most of named entity recog- nition tasks, which extract named entities or events from unstructured data, can be formalized as sequence labeling problems. Sequence labeling has been s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b6fd46354e3b6856127a202183acc7f
https://doi.org/10.1109/icmla.2013.23

ProvenanceCurious: a tool to infer data provenance from scripts

Autor: Mohammad Rezwanul Huq, Peter M. G. Apers, Andreas Wombacher

Publikováno v: Proceedings of the 16th International Conference on Extending Database Technology (EDBT 2013), 765-768
STARTPAGE=765;ENDPAGE=768;TITLE=Proceedings of the 16th International Conference on Extending Database Technology (EDBT 2013)
EDBT

The increasing data volume and highly complex models used in different domains make it difficult to debug models in cases of anomalies. Data provenance provides scientists sufficient information to investigate their models. In this paper, we propose

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61d5acb3ed185ec836ff388013f78b3b
https://research.utwente.nl/en/publications/0c9dbb99-1cf2-49e7-8fa6-fd9f1d1ce5ef