Big Data Integration
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".
Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 13031
Special Issue Editor
Interests: large-scale entity resolution and information integration; personalization; recommender systems; query and data exploration
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The MDPI Information Journal invites submissions to a Special Issue on “Big Data Integration”.
In the big data era, business, government, and scientific organizations’ operations increasingly rely on huge amounts of data collected from several data sources. Such data sources usually exhibit several quality issues, such as incompleteness, redundancy, inconsistency or simply incorrectness. A number of tasks for improving the various aspects of data quality and thus increase the reliability of the outcomes of data analytics are related to data integration. In this Special Issue, we pay special attention to how big data characteristics (such as volume, variety, velocity, and veracity) call for novel data integration frameworks that relax a number of assumptions underlying several methods and techniques proposed in the context of databases, machine learning, and semantic Web communities. Although individual characteristics of big data have been the focus of previous research work in data integration, such techniques are challenged when more than one of the big data characteristics have to be addressed simultaneously.
This Special Issue is concerned with groundbreaking topics at the interface of the data integration problem, with particular emphasis on big data.
Topics of interest include but are not limited to the following:
- Algorithms and techniques for data integration
- End-to-end data integration systems
- Scalable data integration
- Integrating complex data
- Incremental data integration
- Real-time data integration
- Query-based data integration
- Diversity-aware data integration
- Multilingual data integration
- Crowd-based data integration
- Human-in-the-loop data integration
- Transparency in data integration
- Explaining data integration
- Fairness-aware data integration
- Preserving Privacy in data integration
- Semantics and ontologies in data integration
- Entity resolution, record linkage, data matching and duplicate detection
- Blocking for entity resolution
- Distributed entity resolution
- Entity resolution benchmarks
- Data preparation for data integration
- Big data cleaning
- Schema matching
- Schema evolution
- Web content mining
- Web structure mining
- Web usage mining
Dr. Kostas Stefanidis
Guest Editor
Manuscript Submission Information
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