Search Methods for Multidimensional Data

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Search Methods for Multidimensional Data

  1. 1. Abstract Systems Operations Data Partner: System-Wide SafetyNASA and its partners produce staggering amounts of data: and Assurance Technologiespetabytes per day for both earth and space science, with some Customer: Operations and Maintenancemissions producing over a petabyte/day individually. Examining allthe data by hand is clearly impossible; progress has been madein automated discovery, but little has been done to enablethe user to search for potential items of interestdirectly. The goal of our research is to Problem Solutionaddress this gap. No existing technology Our approach is to adapt elements fromStrategic Alignment: adequately several methods to address the problem.OCT Roadmap TA11 (Intelligent • Search begins with supports a user who wants to search forData Understanding, Data • Relevance estimation prototype of anomaly data in today’s vast data sets:Lifecycle elements) concepts from information • System ranksNational Aero R&D Plan • The strict query interpretation in retrieval instead of strict candidates by(organization and mining databases often over- SEARCH constraint application. variation fromof safety data elements) restricts or under- prototypeInitial TRL: 3 restricts the results. METHODS FOR • Multidimensional utility function from utility theory. • System automatically • Data mining does not support ad hoc search as it is not user directed. D MULTIDIMENSIONAL DATA D –––––––––––––––––––––––––––––––––––––– • Query refinement by data expands on user’s mining explicit and implicit initial specification. Shawn Wolfe user feedback. • Information retrieval is Nikunj Oza, PhD • Multiattribute query applied to text, not data. Yi Zhang (UCSC), PhDMartian Images specifications from Safety Reports As a result, the user database Partner: Aviation SafetyPartner: Planetary Data misses important systems. Reporting System SystemCustomer: Scientists items in the Novelty/Contribution Customer: Safety Analysts data. • Decrease difficulty of finding important data • Utilize strengths from multiple technologies • Combine human and machine intelligence Contact: Shawn Wolfe• Search for images by metadata • Search over different field types (numbers, categories, text) Intelligent Systems (TI)• Scientists enter desired values • Fine-tune performance by data mining past queries and (650) 604-4760• Tradeoffs over matching values are used to rank images results <Shawn.Wolfe@nasa.gov> • Users can also provide explicit feedback to refine results

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