@article{924754,
      recid = {924754},
      title = {Analyzing time interval data : introducing an information  system for time interval data analysis /},
      pages = {1 online resource},
      abstract = {Philipp Meisen introduces a model, a query language, and a  similarity measure enabling users to analyze time interval  data. The introduced tools are combined to design and  realize an information system. The presented system is  capable of performing analytical tasks (avoiding any type  of summarizability problems), providing insights, and  visualizing results processing millions of intervals within  milliseconds using an intuitive SQL-based query language.  The heart of the solution is based on several bitmap-based  indexes, which enable the system to handle huge amounts of  time interval data. Contents Modeling Time Interval Data  Querying for Time Interval Data Similarity of Time Interval  Data An Information System for Time Interval Data Analysis  Target Groups Researchers and students in the field of  information management Business analysts and dispatchers in  the fields of online analytical processing (OLAP), data  warehousing (DW), business intelligence (BI), workforce  management, and data science The Author Philipp Meisen  holds a doctoral degree from RWTH Aachen, where he was a  research group leader at the Chair of Information  Management in Mechanical Engineering.},
      url = {http://library.usi.edu/record/924754},
      doi = {https://doi.org/10.1007/978-3-658-15728-9},
}