Method of partitioning data records
DC
First Claim
1. A computer-implemented method of partitioning data records in a computer into groups, comprising the steps of:
- (a) defining a function of a distribution of values of a designated variable associated with the data records, wherein the function comprises a combination of measures of entropy and adjacency, adjacency being weighted by a weighting factor;
(b) partitioning the values of the designated variable into two or more groups, wherein a value of the function is determined by applying an optimization procedure; and
(c) assigning a data record to a group according to the values of the designated variable.
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Abstract
A tree-structured index to multidimensional data is created using occurring patterns and clusters within the data which permit efficient search and retrieval strategies in a database of DNA profiles. A search engine utilizes hierarchical decomposition of the database by identifying clusters of similar DNA profiles and maps to parallel computer architecture, allowing scale up past previously feasible limits. Key benefits of the new method are logarithmic scale up and parallelization. These benefits are achieved by identification and utilization of occurring patterns and clusters within stored data. The patterns and clusters enable the stored data to be partitioned into subsets of roughly equal size. The method can be applied recursively, resulting in a database tree that is balanced, meaning that all paths or branches through the tree have roughly the same length. The method achieves high performance by exploiting the natural structure of the data in a manner that maintains balanced trees. Implementation of the method maps to parallel computer architectures, allowing scale up to very large databases.
61 Citations
23 Claims
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1. A computer-implemented method of partitioning data records in a computer into groups, comprising the steps of:
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(a) defining a function of a distribution of values of a designated variable associated with the data records, wherein the function comprises a combination of measures of entropy and adjacency, adjacency being weighted by a weighting factor; (b) partitioning the values of the designated variable into two or more groups, wherein a value of the function is determined by applying an optimization procedure; and (c) assigning a data record to a group according to the values of the designated variable. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computer-implemented method of partitioning data records of a database in a computer, wherein the database is indexed using a tree of nodes, wherein the tree of nodes comprises a root node which is connected to two or more branches originating at the root node, wherein each branch terminates at a node, wherein each node other than the root node is a non-terminal node or a leaf node, wherein each non-terminal node is connected to two or more branches originating at the non-terminal node and terminating at a node, wherein the tree-structured index comprises one or more qiueries associated with each non-terminal node, said method comprising the steps of:
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(a) identifying occurring sets of clusters in the data records of the database; (b) defining for each identified set of clusters a query that evaluates one of a Boolean expression or a decision tree and assigns each data record within the set of clusters, wherein said qiueries are determined by a combination of measures of entropy and adjacency, adjacency being weighted by a weighting factor; and (c) associating each query defined in step (b) with a non-terminal node and an associated set of clusters identified in step (a), and associating with each cluster within the set of clusters one branch originating at the non-terminal node, said branch forming part of one or more paths leading to leaf nodes comprising the data records assigned to the cluster by the query. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23)
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Specification
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- Resources
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Current AssigneeUniversity of Tennessee Research Foundation (University of Tennessee)
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Original AssigneeUniversity of Tennessee Research Foundation (University of Tennessee)
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InventorsBirdwell, John D., Wang, Tse-Wei, Horn, Roger D., Yadav, Puneet, Icove, David J.
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Primary Examiner(s)Wong, Don
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Assistant Examiner(s)NGUYEN, MERILYN P
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Application NumberUS10/767,730Publication NumberTime in Patent Office1,327 DaysField of Search707/4, 707/5, 707/6, 707/101, 707/100, 707/104.1, 706/12, 703/2, 715/850US Class Current1/1CPC Class CodesG06F 16/2246 Trees, e.g. B+treesG06F 16/2264 Multidimensional index stru...G06F 16/285 Clustering or classificationG16B 40/00 ICT specially adapted for b...G16B 40/30 Unsupervised data analysisG16B 50/00 ICT programming tools or da...G16B 50/20 Heterogeneous data integrationY10S 707/99932 Access augmentation or opti...Y10S 707/99933 Query processing, i.e. sear...Y10S 707/99935 Query augmenting and refini...Y10S 707/99942 Manipulating data structure...Y10S 707/99945 Object-oriented database st...
