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Title: Method of locating related items in a geometric space for data mining

Abstract

A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method is especially beneficial for communicating databases with many items, and with non-regular relationship patterns. Examples of such databases include databases containing items such as scientific papers or patents, related by citations or keywords. A computer system adapted for practice of the present invention can include a processor, a storage subsystem, a display device, and computer software to direct the location and display of the entities. The method comprises assigning numeric values as a measure of similarity between each pairing of items. A matrix is constructed, based on the numeric values. The eigenvectors and eigenvalues of the matrix are determined. Each item is located in the geometric space at coordinates determined from the eigenvectors and eigenvalues. Proper construction of the matrix and proper determination of coordinates from eigenvectors can ensure that distance between items in the geometric space is representative of the numeric value measure of the items' similarity.

Inventors:
 [1]
  1. (Albuquerque, NM)
Publication Date:
Research Org.:
SANDIA CORP
OSTI Identifier:
872419
Patent Number(s):
US 5930784
Assignee:
Sandia Corporation (Albuquerque, NM) SNL
DOE Contract Number:
AC04-94AL85000
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
method; locating; related; items; geometric; space; data; mining; transforms; relationships; locations; locates; distance; corresponds; degree; relatedness; facilitates; communication; structure; especially; beneficial; communicating; databases; non-regular; relationship; patterns; examples; containing; scientific; papers; citations; keywords; computer; adapted; practice; processor; storage; subsystem; display; device; software; direct; location; entities; comprises; assigning; numeric; values; measure; similarity; pairing; matrix; constructed; based; eigenvectors; eigenvalues; determined; item; located; coordinates; proper; construction; determination; ensure; representative; value; method comprises; display device; related items; method comprise; geometric space; data mining; communicating data; locating related; /707/

Citation Formats

Hendrickson, Bruce A. Method of locating related items in a geometric space for data mining. United States: N. p., 1999. Web.
Hendrickson, Bruce A. Method of locating related items in a geometric space for data mining. United States.
Hendrickson, Bruce A. 1999. "Method of locating related items in a geometric space for data mining". United States. doi:. https://www.osti.gov/servlets/purl/872419.
@article{osti_872419,
title = {Method of locating related items in a geometric space for data mining},
author = {Hendrickson, Bruce A.},
abstractNote = {A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method is especially beneficial for communicating databases with many items, and with non-regular relationship patterns. Examples of such databases include databases containing items such as scientific papers or patents, related by citations or keywords. A computer system adapted for practice of the present invention can include a processor, a storage subsystem, a display device, and computer software to direct the location and display of the entities. The method comprises assigning numeric values as a measure of similarity between each pairing of items. A matrix is constructed, based on the numeric values. The eigenvectors and eigenvalues of the matrix are determined. Each item is located in the geometric space at coordinates determined from the eigenvectors and eigenvalues. Proper construction of the matrix and proper determination of coordinates from eigenvectors can ensure that distance between items in the geometric space is representative of the numeric value measure of the items' similarity.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 1999,
month = 1
}

Patent:

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  • A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method is especially beneficial for communicating databases with many items, and with non-regular relationship patterns. Examples of such databases include databases containing items such as scientific papers or patents, related by citations or keywords. A computer system adapted for practice of the present invention can include a processor, amore » storage subsystem, a display device, and computer software to direct the location and display of the entities. The method comprises assigning numeric values as a measure of similarity between each pairing of items. A matrix is constructed, based on the numeric values. The eigenvectors and eigenvalues of the matrix are determined. Each item is located in the geometric space at coordinates determined from the eigenvectors and eigenvalues. Proper construction of the matrix and proper determination of coordinates from eigenvectors can ensure that distance between items in the geometric space is representative of the numeric value measure of the items' similarity. 12 figs.« less
  • A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method makes use of numeric values as a measure of similarity between each pairing of items. The items are given initial coordinates in the space. An energy is then determined for each item from the item's distance and similarity to other items, and from the density of items assignedmore » coordinates near the item. The distance and similarity component can act to draw items with high similarities close together, while the density component can act to force all items apart. If a terminal condition is not yet reached, then new coordinates can be determined for one or more items, and the energy determination repeated. The iteration can terminate, for example, when the total energy reaches a threshold, when each item's energy is below a threshold, after a certain amount of time or iterations.« less
  • A leak detecting microphone inserted directly into fluid within a pipe includes a housing having a first end being inserted within the pipe and a second opposed end extending outside the pipe. A diaphragm is mounted within the first housing end and an acoustic transducer is coupled to the diaphragm for converting acoustical signals to electrical signals. A plurality of apertures are provided in the housing first end, the apertures located both above and below the diaphragm, whereby to equalize fluid pressure on either side of the diaphragm. A leak locating system and method are provided for locating fluid leaksmore » within a pipe. A first microphone is installed within fluid in the pipe at a first selected location and sound is detected at the first location. A second microphone is installed within fluid in the pipe at a second selected location and sound is detected at the second location. A cross-correlation is identified between the detected sound at the first and second locations for identifying a leak location.« less
  • A method of data mining represents related items in a multidimensional space. Distance between items in the multidimensional space corresponds to the extent of relationship between the items. The user can select portions of the space to perceive. The user also can interact with and control the communication of the space, focusing attention on aspects of the space of most interest. The multidimensional spatial representation allows more ready comprehension of the structure of the relationships among the items.