@conference {17162, title = {Finding comparable temporal categorical records: A similarity measure with an interactive visualization}, booktitle = {IEEE Symposium on Visual Analytics Science and Technology, 2009. VAST 2009}, year = {2009}, month = {2009/10/12/13}, pages = {27 - 34}, publisher = {IEEE}, organization = {IEEE}, abstract = {An increasing number of temporal categorical databases are being collected: Electronic Health Records in healthcare organizations, traffic incident logs in transportation systems, or student records in universities. Finding similar records within these large databases requires effective similarity measures that capture the searcher{\textquoteright}s intent. Many similarity measures exist for numerical time series, but temporal categorical records are different. We propose a temporal categorical similarity measure, the M\&M (Match \& Mismatch) measure, which is based on the concept of aligning records by sentinel events, then matching events between the target and the compared records. The M\&M measure combines the time differences between pairs of events and the number of mismatches. To accom-modate customization of parameters in the M\&M measure and results interpretation, we implemented Similan, an interactive search and visualization tool for temporal categorical records. A usability study with 8 participants demonstrated that Similan was easy to learn and enabled them to find similar records, but users had difficulty understanding the M\&M measure. The usability study feedback, led to an improved version with a continuous timeline, which was tested in a pilot study with 5 participants.}, keywords = {data visualisation, Educational institutions, Feedback, Information retrieval, interactive search tool, interactive systems, interactive visualization tool, large databases, M\&M Measure, Match \& Mismatch measure, Medical services, numerical time series, parameters customization, Particle measurements, Similan, similarity measure, Similarity Search, temporal categorical databases, Temporal Categorical Records, temporal databases, Testing, Time measurement, time series, transportation, usability, very large databases, visual databases, Visualization}, isbn = {978-1-4244-5283-5}, doi = {10.1109/VAST.2009.5332595}, author = {Wongsuphasawat,K. and Shneiderman, Ben} } @conference {17056, title = {Design and evaluation of incremental data structures and algorithms for dynamic query interfaces}, booktitle = {IEEE Symposium on Information Visualization, 1997. Proceedings}, year = {1997}, month = {1997/10/21/21}, pages = {81 - 86}, publisher = {IEEE}, organization = {IEEE}, abstract = {A dynamic query interface (DQI) is a database access mechanism that provides continuous real-time feedback to the user during query formulation. Previous work shows that DQIs are elegant and powerful interfaces to small databases. Unfortunately, when applied to large databases, previous DQI algorithms slow to a crawl. We present a new incremental approach to DQI algorithms and display updates that work well with large databases, both in theory and in practice.}, keywords = {Algorithm design and analysis, Bars, Computer science, continuous real-time feedback, Data structures, data visualisation, Data visualization, database access mechanism, Displays, DQI algorithms, dynamic query interfaces, Feedback, Graphical user interfaces, Heuristic algorithms, incremental data structures, Information Visualization, large databases, Manipulator dynamics, NASA, query formulation, query languages, Query processing, real-time systems, small databases, User interfaces, very large databases, visual databases, visual languages}, isbn = {0-8186-8189-6}, doi = {10.1109/INFVIS.1997.636790}, author = {Tanin,E. and Beigel,R. and Shneiderman, Ben} } @article {16740, title = {ADMS: a testbed for incremental access methods}, journal = {IEEE Transactions on Knowledge and Data Engineering}, volume = {5}, year = {1993}, month = {1993/10//}, pages = {762 - 774}, abstract = {ADMS is an advanced database management system developed-to experiment with incremental access methods for large and distributed databases. It has been developed over the past eight years at the University of Maryland. The paper provides an overview of ADMS, and describes its capabilities and the performance attained by its incremental access methods. This paper also describes an enhanced client-server architecture that allows an incremental gateway access to multiple heterogeneous commercial database management systems}, keywords = {Add-drop multiplexers, ADMS, advanced database management system, client-server architecture, commercial database management systems, Computational modeling, Database systems, distributed databases, heterogeneous DBMS, incremental access methods, incremental gateway, Information retrieval, interoperability, join index, large databases, Navigation, network operating systems, Object oriented databases, Object oriented modeling, Query processing, System testing, very large databases, view index, Workstations}, isbn = {1041-4347}, doi = {10.1109/69.243508}, author = {Roussopoulos, Nick and Economou,N. and Stamenas,A.} }