ADAPTIVE TREE STRUCTURE FOR VISUALIZING DATA
First Claim
1. A method for generating an adaptive tree structure based upon data density of an event dataset comprising a plurality of raw events, comprising:
- specifying a first level within an adaptive tree structure, the first level comprising a root node assigned a threshold number of summary events from an event dataset, a time span of the root node corresponding to a total time span of the event dataset, the root node designated as a summary node; and
specifying one or more additional levels within the adaptive tree structure, the specifying comprising;
for a current level of the adaptive tree structure;
determining whether a previous level immediately before the current level comprises one or more summary nodes; and
if the previous level comprises one or more summary nodes, then for respective summary nodes;
generating a predetermined number of child nodes for a summary node, a time span of a child node corresponding to fraction of a time span of the summary node; and
for respective child nodes;
if a number of raw events within the event dataset covered by a time span of a child node is less than or equal to the threshold number, then designating the child node as a raw node and assigning the raw events to the raw node, else designating the child node as a summary node and assigning a number of summary events derived from raw events within the event dataset covered by the time span of the child node, the number of summary events equal to the threshold number.
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Accused Products
Abstract
One or more systems and/or techniques for generating an adaptive tree structure for storing event data based upon data density of events are disclosed. In particular, the adaptive tree structure may comprise one or more levels of nodes, where a level may correspond to a resolution of events. Nodes may correspond to particular time spans over which event data was recorded. A node may be designated as a raw node comprising raw events or a summary node comprising summary events based upon the number of events occurring within a time span covered by the node.
29 Citations
20 Claims
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1. A method for generating an adaptive tree structure based upon data density of an event dataset comprising a plurality of raw events, comprising:
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specifying a first level within an adaptive tree structure, the first level comprising a root node assigned a threshold number of summary events from an event dataset, a time span of the root node corresponding to a total time span of the event dataset, the root node designated as a summary node; and specifying one or more additional levels within the adaptive tree structure, the specifying comprising; for a current level of the adaptive tree structure; determining whether a previous level immediately before the current level comprises one or more summary nodes; and if the previous level comprises one or more summary nodes, then for respective summary nodes; generating a predetermined number of child nodes for a summary node, a time span of a child node corresponding to fraction of a time span of the summary node; and for respective child nodes;
if a number of raw events within the event dataset covered by a time span of a child node is less than or equal to the threshold number, then designating the child node as a raw node and assigning the raw events to the raw node, else designating the child node as a summary node and assigning a number of summary events derived from raw events within the event dataset covered by the time span of the child node, the number of summary events equal to the threshold number. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A system for generating an adaptive tree structure based upon density of an event dataset comprising a plurality of raw events, comprising:
an adaptive tree generator configured to; specify a first level within an adaptive tree structure, the first level comprising a root node assigned a threshold number of summary events from an event dataset, a time span of the root node corresponding to a total time span of the event dataset, the root node designated as a summary node; and specify one or more additional levels within the adaptive tree structure, the specifying comprising; for a current level of the adaptive tree structure; determine whether a previous level immediately before the current level comprises one or more summary nodes; and if the previous level comprises one or more summary nodes, then for respective summary nodes; generate a predetermined number of child nodes for a summary node, a time span of a child node corresponding to fraction of a time span of the summary node; and for respective child nodes;
if a number of raw events within the event dataset covered by a time span of a child node is less than or equal to the threshold number, then designate the child node as a raw node and assigning the raw events to the raw node, else designate the child node as a summary node and assigning a number of summary events derived from raw events within the event dataset covered by the time span of the child node, the number of summary events equal to the threshold number.- View Dependent Claims (13, 14, 15, 16)
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17. A method for determining node data corresponding to events, comprising:
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receiving a requested time span; calculating a level (L) corresponding to; - View Dependent Claims (18, 19, 20)
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Specification