Informace o projektu
Big Data Analytics for Unstructured Data
(Big Data Analytics for Unstructured Data)
- Kód projektu
- GA16-18889S
- Období řešení
- 1/2016 - 12/2018
- Investor / Programový rámec / typ projektu
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Grantová agentura ČR
- Standardní projekty
- Fakulta / Pracoviště MU
- Fakulta informatiky
Development of new foundations for Big Data Analytics requires an effective and efficient content-based access to data that is prevalently unstructured. For this data, to achieve the needed integration of large-scale knowledge discovery techniques with statistical modelling, it is necessary to first uncover descriptive knowledge of complex and heterogeneous objects to make them findable. Then, scalable search structures are needed to efficiently execute similarity access operations, considering also simultaneous execution of multiple queries. Such supporting technologies should serve for semantic data integration and enrichment technologies able to make sense of Big Data for high-level services. We plan to elaborate on these topics and report results, supported by advanced prototype implementations, in respective scientific publication platforms.
Publikace
Počet publikací: 15
2019
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Searching for Variable-Speed Motions in Long Sequences of Motion Capture Data
Information Systems, rok: 2019, ročník: 80, vydání: February, DOI
2018
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Combining Cache and Priority Queue to Enhance Evaluation of Similarity Search Queries
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, rok: 2018
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Continuous Time-Dependent kNN Join by Binary Sketches
IDEAS 2018 : 22nd International Database Engineering & Applications Symposium, June 18-20, 2018, Villa San Giovanni, Italy, rok: 2018
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Multi-modal Image Retrieval for Search-based Image Annotation with RF
2018 IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM 2018), rok: 2018
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Speeding up Continuous kNN Join by Binary Sketches
Advances in Data Mining, rok: 2018
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Towards Artificial Priority Queues for Similarity Query Execution
2018 IEEE 34th International Conference on Data Engineering Workshops (ICDEW), rok: 2018
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Towards Faster Similarity Search by Dynamic Reordering of Streamed Queries
Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXVIII, rok: 2018
2017
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A Real-Time Annotation of Motion Data Streams
19th IEEE International Symposium on Multimedia, rok: 2017
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Cache and Priority Queue Based Approximation Technique for a Stream of Similarity Search Queries
Similarity Search and Applications : 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings, rok: 2017
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Fusion Strategies for Large-Scale Multi-modal Image Retrieval
Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXIII, rok: 2017