Source: http://www.google.com/patents/US20040181519?ie=ISO-8859-1
Timestamp: 2014-08-27 11:44:01
Document Index: 7994121

Matched Legal Cases: ['art 512', 'art. 508', 'art. 514', 'art. 516', 'art 1206', 'art, 1408']

Patent US20040181519 - Method for generating multidimensional summary reports from multidimensional ... - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign in<nobr>Advanced Patent Search</nobr>PatentsA method for locating data anomalies (exceptions) in a multi-dimensional data cube is disclosed, where the method uses certain properties called anti-monotone constraints of aggregated data in the cube to reduce the search space during data analysis and anomaly detection....http://www.google.com/patents/US20040181519?utm_source=gb-gplus-sharePatent US20040181519 - Method for generating multidimensional summary reports from multidimensional summary reports from multidimensional dataAdvanced Patent SearchPublication numberUS20040181519 A1Publication typeApplicationApplication numberUS 10/483,304PCT numberPCT/US2002/021538Publication dateSep 16, 2004Filing dateJul 9, 2002Priority dateJul 9, 2002Publication number10483304, 483304, PCT/2002/21538, PCT/US/2/021538, PCT/US/2/21538, PCT/US/2002/021538, PCT/US/2002/21538, PCT/US2/021538, PCT/US2/21538, PCT/US2002/021538, PCT/US2002/21538, PCT/US2002021538, PCT/US200221538, PCT/US2021538, PCT/US221538, US 2004/0181519 A1, US 2004/181519 A1, US 20040181519 A1, US 20040181519A1, US 2004181519 A1, US 2004181519A1, US-A1-20040181519, US-A1-2004181519, US2004/0181519A1, US2004/181519A1, US20040181519 A1, US20040181519A1, US2004181519 A1, US2004181519A1InventorsMohammed Shahbaz AnwarOriginal AssigneeMohammed Shahbaz AnwarExport CitationBiBTeX, EndNote, RefManReferenced by (15), Classifications (5) External Links: USPTO, USPTO Assignment, EspacenetMethod for generating multidimensional summary reports from multidimensional summary reports from multidimensional dataUS 20040181519 A1Abstract A method for locating data anomalies (exceptions) in a multi-dimensional data cube is disclosed, where the method uses certain properties called anti-monotone constraints of aggregated data in the cube to reduce the search space during data analysis and anomaly detection. Images(34) Claims(20)
[0117] A non-limiting list of benefits of Pareto analysis include: (1) when the user wants to solve a business or personal problem by identifying the most important causes of the problem; (2) when the user wants to identify which products to discontinue in a product line; (3) when the user wants to reduce the business costs; (4) when the user feels that too much information must be analyzed before a decision can be made; (5) when the user wants to make an economical use of the resources; or (6) when the user want to improve the service offered to the customers. [0118] To summarize, numerous people, over the centuries, have observed the existence of the phenomenon of vital few and trivial many as it applied to their local sphere of activity. Pareto observed this phenomenon as applied to distribution of wealth, and advanced the theory of a logarithmic law of income distribution to fit the phenomenon. Lorenz developed a form of cumulative curve to depict the distribution of wealth graphically. Juran was (seemingly) the first to identify the phenomenon of the vital few and trivial many as a �universal,� applicable to many fields. Juran applied the name �The Pareto Principe� to this universal phenomenon. Juran also coined the phrase �vital few and trivial many� and applied the Lorenz curves to depict this universal phenomenon in graphic form. [0119] Referring now to FIG. 5, a screen 500 is a representation of the integration of Pareto chart 512 and a cross-tab 502. 504 is the column axis (also known as y-axis) of the cross-tab. 504 is represented by 506 in the Pareto chart. 508 is the row axis (also known as x-axis) of the cross-tab. 508 is represented by 510 in the Pareto chart. 514 is a slider that controls the percent of data shown in the Pareto chart. 516 is a legend to show the row and column information. The column of data 518 is shown by 520 bar in the Pareto chart. The row of data 524 is shown by 522 bar in the Pareto chart. [0120]FIG. 6 shows the interaction between the bar 602 of the Pareto chart and the row 604 of the cross-tab when the mouse cursor is over 602. Additional information is shown in the form of a balloon text 600. [0121]FIG. 7 shows the response of the point 706 of the Pareto chart when mouse cursor is over it. The statistics is displayed in the form of a balloon text 704. The cumulative percent of bar 708 and 710 is shown. Bar 708 is the representation of row 712, and bar 710 is the representation of row 714. Line curve 700 shows the cumulative percent for the column data 718, while line curve 702 shows the cumulative percent for the row data 716. [0122]FIG. 8 shows the response of the Pareto charts when slider 810 is manipulated with a pointing device, e.g., a mouse. When the slider thumb 806 is moved with a mouse click-and-drag action, the slider 808 shows the percent of visible data. The row Pareto chart responds by collapsing the scrolled-of data with a bar called �rest� 804. Like the column Pareto chart responds by collapsing the scrolled-of data with a bar called �rest� 802. [0123] Referring now to FIG. 9A, when a mouse right-click is performed on a �rest� bar 904 or 906, a short-cut menu 908 is displayed. The user can select �hide� 902 with a mouse left-click. As a response to this action the �rest� bars 904 and 906 are hidden, i.e. not displayed. FIG. 9B shows the response to a 902 �hide� operation. [0124]FIG. 10 shows the response to a mouse-over a cell 1006 in the cross-tab. The column Pareto chart responds by highlighting the bar 1002 which corresponds to the column header 1004 in the cross-tab. The column header 1004 is also matched with 1016 highlight. Additionally, the total sum for the column is displayed by 1018. The row Pareto chart responds by highlighting the bar 1012 which corresponds to the row header 1008 in the cross-tab. The row header 1008 is also matched with 1010 highlight. Additionally, the total sum for the row is displayed by 1014. [0125]FIG. 11 shows the Traffic Light functionality implemented in Pareto charts. This functionality can be turned on or off from 1102 button. When Traffic Light is turned on, a Target (horizontal) line 1104 and 1108 appear on the charts. The placement of bar is based on a calculation like mean, median, or some user defined function. The Target line can be moved up or down with a mouse. Traffic light symbols 1112, 1110 and 1106 appear on each bar of the Pareto chart. The color shown in each traffic light symbol can either be red, yellow or green depending upon the value of the bar in relationship to the Target line 1104 or 1108. The color of traffic light symbol will change as the Target line 1104 or 1108 is moved up or down. [0126]FIG. 12 shows the functionality where one or the other Pareto chart can be hidden. In this case the button 1204 of the legend 1202 has been toggled off. As a result on row Pareto chart 1206 is shown, while column Pareto chart is hidden. [0127]FIG. 13 shows the functionality where three dimensions are shown in Pareto chart. When a dimension 1312 and 1314 is placed to the left of Dimension Separator 1310, the Pareto chart is split 1302 and 1304 to appropriately represent the third dimension. 1302, 1318 and 1316 comprise of one group, while 1304, 1306 and 1308 comprise the other group. [0128]FIG. 14 shows the interaction between Pareto chart and cross-tab when three dimensions 1412, 1414 and 1416 are represented. When a mouse cursor is placed over 1404 in Pareto chart, 1408 is highlighted in cross-tab. Balloon text 1406 is also shown. The 1414 block of cross-tab is represented by 1402 block of Pareto chart. [0129]FIG. 15 shows the response when column Pareto chart is turned off by clicking on 1502 column button. In this Pareto chart only row data is shown, while column data is hidden (i.e. not shown). [0130]FIG. 16A shows the property dialog 1602 for Traffic Light. Traffic Light can be turned on or off with 1604. The color red or green is context dependent, in some context more (above) is better, while in other context less (below) is better. The appropriate context mode can be set with 1606. The Target line placement can be determined with 1608. The tolerance by which to change color can be controlled with 1610. FIG. 16B shows the Target line placement 1608 options. FIG. 16C shows the Traffic Light mode 1606 options. [0131] All references cited herein are incorporated by reference. While this invention has been described fully and completely, it should be understood that, within the scope of the appended claims, the invention may be practiced otherwise than as specifically described. Although the invention has been disclosed with reference to its preferred embodiments, from reading this description those of skill in the art may appreciate changes and modification that may be made which do not depart from the scope and spirit of the invention as described above and claimed hereafter. Referenced byCiting PatentFiling datePublication dateApplicantTitleUS7162489 *Dec 12, 2005Jan 9, 2007Microsoft CorporationAnomaly detection in data perspectivesUS7219093 *Dec 2, 2004May 15, 2007Proclarity CorporationSystem and method for generating custom hierarchies in an analytical data structureUS7243100 *Jul 30, 2003Jul 10, 2007International Business Machines CorporationMethods and apparatus for mining attribute associationsUS7418438Nov 30, 2004Aug 26, 2008International Business Machines CorporationAutomated default dimension selection within a multidimensional enterprise software systemUS7505888Nov 30, 2004Mar 17, 2009International Business Machines CorporationReporting model generation within a multidimensional enterprise software systemUS7593955 *Nov 30, 2004Sep 22, 2009International Business Machines CorporationGeneration of aggregatable dimension information within a multidimensional enterprise software systemUS7610284 *Nov 27, 2006Oct 27, 2009Industry-Academic Cooperation Foundation, Yonsei UniversityCompressed prefix trees and estDec+ method for finding frequent itemsets over data streamsUS7610300Nov 30, 2004Oct 27, 2009International Business Machines CorporationAutomated relational schema generation within a multidimensional enterprise software systemUS7707207 *Feb 17, 2006Apr 27, 2010Microsoft CorporationRobust cardinality and cost estimation for skyline operatorUS7747564 *Jun 22, 2006Jun 29, 2010International Business Machines CorporationComparative analysis of business intelligence dataUS8131533Jan 8, 2009Mar 6, 2012International Business Machines CorporationReporting model generation within a multidimensional enterprise software systemUS8615511Jan 20, 2012Dec 24, 2013Operational Transparency LLCData visualization interfaceUS20120159312 *Dec 17, 2010Jun 21, 2012Microsoft CorporationRepresentation of an interactive document as a graph of entitiesUS20120271837 *Apr 21, 2011Oct 25, 2012Kryger Lisa MIntelligent data filteringWO2006059243A2 *Nov 16, 2005Jun 8, 2006Cognos IncAggregatable dimension information fn multidimensional enterprise software system* Cited by examinerClassifications U.S. Classification1/1, 707/999.003International ClassificationG06F17/30Cooperative ClassificationG06F17/30592European ClassificationG06F17/30S8MRotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services©2012 Google