Database, Programming and Web Technologies

  • Selma Lagerlöfs Vej 300, Cassiopeia

    9220 Aalborg

    Danmark

Organisationsprofil

Organisationsprofil

Database, programming and web technologies is one of the three research groups at the Department of Computer Science. The group covers 

  • Data-intensive systems
  • Programming
  • Web science and engineering

In the area of data-intensive systems, substantial research concerns aspects of Big Data. Central research topics include temporal, spatial, and spatio-temporal data management, and mobile data management; additional prominent topics include business intelligence, data analytics, data warehousing, data integration, OLAP, multidimensional databases, and data mining. Within these topics, the research covers modeling and database design, data models, query processing, indexing, and applications.

In the area of programming technology the research concerns general-purpose programming languages as well as special-purpose languages, e.g., for embedded, real-time, mobile, parallel, distributed, and data-intensive systems. Studies also cover theories, environments and tool support for program development and analysis.

In the area of web science and engineering, the research concerns web personalization, web data management and querying, recommender systems, semantic web and (linked) open data, information retrieval, web and social media mining, web engineering, and knowledge mining and integration. The research also extends to digital humanities and computational social science.

The research approach is primarily constructive: theoretically well-founded, purposeful artefacts such as frameworks, data structures, indexes, algorithms, languages, tools, and systems are prototyped and subjected to empirical study. Further, the research is mostly driven by current and anticipated future real-world applications, with primary application areas being intelligent transport systems, web querying, logistics, energy grids, and healthcare.

In the area of programming technology the research concerns general-purpose programming languages as well as special-purpose languages, e.g., for embedded, real-time, mobile, parallel, distributed, and data-intensive systems. Studies also cover theories, environments and tool support for program development and analysis.

In the area of web science and engineering, the research concerns web personalization, web data management and querying, recommender systems, semantic web and (linked) open data, information retrieval, web and social media mining, web engineering, and knowledge mining and integration. The research also extends to digital humanities and computational social science.

The research approach is primarily constructive: theoretically well-founded, purposeful artefacts such as frameworks, data structures, indexes, algorithms, languages, tools, and systems are prototyped and subjected to empirical study. Further, the research is mostly driven by current and anticipated future real-world applications, with primary application areas being intelligent transport systems, web querying, logistics, energy grids, and healthcare.

For more information see 
DPW webpage
Daisy webpage

Fingeraftryk Fingeraftrykket er baseret på teksten fra de videnskabelige dokumenter, der er relateret til de tilknyttede personer. Baseret på dette oprettes et indeks af vægtede ord, der definerer de vigtigste emner i forskningsenheden

Data warehouses Teknik og materialevidenskab
Query processing Teknik og materialevidenskab
Trajectories Teknik og materialevidenskab
Location based services Teknik og materialevidenskab
Processing Teknik og materialevidenskab
Global positioning system Teknik og materialevidenskab
Travel time Teknik og materialevidenskab
Semantics Teknik og materialevidenskab

Netværk Klik på punkterne for at se detaljerne.

Projekter 2008 2023

Algorithmic Foundations for Data-Intensive Routing

Yang, B.

01/03/201928/02/2021

Projekter: ProjektAndet

Astra: Analytics of Time series in spatial networks

Yang, B.

01/10/201830/09/2021

Projekter: ProjektForskning

aSTEP: aau's Spatio-TEmporal data analytics Platform

Yang, B.

01/02/2016 → …

Projekter: ProjektForskning

Publikationer 2011 2019

AMIC: An Adaptive Information Theoretic Method to Identify Multi-Scale Temporal Correlations in Big Time Series Data

Ho, N. T. T., Vo, H., Vu, M. & Pedersen, T. B., 19 mar. 2019, (Accepteret/In press) I : IEEE Transactions on Big Data.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Fil

An MBR-Oriented Approach for Efficient Skyline Query Processing

Zhang, J., Wang, W., Jiang, X., Ku, W-S. & Lu, H., 2019, (Accepteret/In press) The 35th IEEE International Conference on Data Engineering (ICDE). IEEE, (Proceedings of the International Conference on Data Engineering).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

An Overlapping Voronoi Diagram-based System for Multi-Criteria Optimal Location Queries

Zhang, J., Harn, P-W., Ku, W-S., Sun, M-T., Qin, X., Lu, H. & Jiang, X., 2019, (Accepteret/In press) I : Geoinformatica.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Priser

Best Demo Award

Ove Andersen (Modtager) & Kristian Torp (Modtager), 7 nov. 2018

Pris: Priser, stipendier, udnævnelser

Best demo at MDM 2013

Bin Yang (Modtager), 2013

Pris: Priser, stipendier, udnævnelser

Best paper at MDM 2013

Bin Yang (Modtager), 2013

Pris: Priser, stipendier, udnævnelser

Presse/medie

Modeltog viser vejen til machine learning i cloud'en

Nurefsan Gür

19/03/2019

2 elementer af mediedækning

Presse/medie

Kunstig intelligens skal hjælpe Bring med at ruteoptimere

Bin Yang

18/01/2019

1 element af mediedækning

Presse/medie

Kunstig intelligens gør trafikken smartere

Bin Yang

21/12/2018

1 element af mediedækning

Presse/medie