System and method for searching through a graphic user interface

• US 8,997,008 B2
• Filed: 07/17/2012
• Issued: 03/31/2015
• Est. Priority Date: 07/17/2012
• Status: Active Grant

• Current Assignee: Priority Jobs Ltd
• Original Assignee: Pelicans Networks Ltd.
• Inventors: Finkel, Yaron, Waisbein, Leon
• Primary Examiner(s): Chow, Doon
• Assistant Examiner(s): CHIUSANO, ANDREW TSUTOMU
• Application Number:
  US13/550,716
• Publication Number:
  US 20140026083A1
• Time in Patent Office: 987 Days
• Field of Search: 715/763, 715/833, 715/834, 715/968, 715/974, 707/749
• US Class Current: 715/763
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/90328 using search space presentation or visualization, e.g. category or range presentation and selection
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials

Abstract

A computer-implemented method for constructing and manipulating a Graphic User Interface (GUI), comprising retrieving from a data repository first GUI data representing at least (i) an entity, (ii) attributes of an entity, (iii) a manipulatable scale associated with a respective attribute; constructing on a screen the GUI including converting the first GUI data into displayable GUI data which include at least the entity, its attributes and for at least one of the attributes a manipulatable scale and displaying the displayable GUI data; enabling a user to perform on the GUI a manipulation of at least one manipulatable scale of a respective attribute giving rise to manipulated displayable GUI data; converting the manipulated displayable GUI data into second GUI data representing at least one data record; and using the at least one data record or portion thereof for operations in the data repository.

Claims

1. A computer-implemented method for comparing similarity between an entity of interest and a candidate entity, said method comprising:

a) retrieving from a data repository data records representing said entity of interest and said candidate entity, said data records include at least attribute data, scale data and group operation data, wherein the attribute data representing attributes of said entity of interest and said candidate entity, the scale data representing scales associated with respective attributes and signifying levels of significance of said respective attributes, said attributes being classified into groups, said group operation data being indicative of different group operations within said groups, said attributes associated with said scales forming predetermined shapes on a Graphic User Interface (GUI) representing said entity of interest and said candidate entity;

b) comparing scale data associated with each attribute of said entity of interest with scale data associated with the same attribute of said candidate entity, selecting the smaller scale of the comparison as Attribute Compare Score for each attribute;

c) calculating a Group Score for each group of said groups, including;

if the group operation data of a group is set to OR, calculating a ratio of the largest Attribute Compare Score within said group to the maximum scale of attributes of the group, setting the ratio as the Group Score;

otherwise the group operation data of the group is set to AND, calculating a ratio of a sum of Attribute Compare Scores of the group to a sum of the scale data associated with the attributes of said entity of interest, setting the ratio as the Group Score; and

d) summing up Group Scores of said groups as a Shape Match Score, representing a similarity indication between said entity of interest and said candidate entity.

2. A computer-implemented method for comparing similarity between an entity of interest and a candidate entity, said method comprising:

a) retrieving from a data repository data records representing said entity of interest and said candidate entity, said data records include at least attribute data, scale data and group operation data, wherein the attribute data representing attributes of said entity of interest and said candidate entity, the scale data representing scales associated with respective attributes and signifying levels of significance of said respective attributes, said attributes being classified into groups, said group operation data being indicative of different group operations within said groups, said attributes associated with said scales forming predetermined shapes on a Graphic User Interface (GUI) representing said entity of interest and said candidate entity;

said attributes being hierarchical and associated with respective shapes of their own characterized by sub-attributes of said attributes and scales of said sub-attributes, thereby forming layers of said shapes to represent said entity of interest and said candidate entity, assigning weights respectively to said sub-attributes, said attributes, said groups and said shapes;

b) from the most outer layer of said shapes, for each sub-attribute, calculating a ratio of a sub-attribute weight to a sum of all sub-attribute weights within a respective group, applying the ratio of each sub-attribute weight to the scale data of the sub-attribute, giving rise to a weighted scale data, comparing the weighted scale data of the sub-attribute of said entity of interest to the weighted scale data of the same sub-attribute of said candidate entity, and selecting the smaller scale of the comparison as Attribute Compare Score for each sub-attribute;

c) for each group of said groups,

i) calculating a Group Score, including;

if the group operation of a group that is set to OR, calculating a ratio of the largest Attribute Compare Score within said group to the maximum scale of sub-attributes of said group, setting the ratio as the Group Score;

otherwise the group operation of the group is set to AND, calculating a ratio of a sum of Attribute Compare Scores of the group to a sum of the scale data of the sub-attributes of said entity of interest, setting the ratio as the Group Score, calculating all Group Scores; and

ii) calculating a ratio of a group weight of said group to the sum of all group weights, applying the ratio of each group weight to the respective Group Score, giving rise to a Weighted Group Score;

d) summing up Weighted Group Scores of said groups in a shape as a Shape Match Score, calculating all Shape Match Scores for shapes in the most outer layer that are drilled down from the same inner shape, calculating Shape Match Score for said inner shape, calculating a ratio of a shape weight to a sum of all shape weights in said most outer layer together with the inner shape weight, applying the ratio of each shape weight to the respective Shape Match Score, giving rise to a Weighted Shape Match Score for the inner shape, calculating Weighted Shape Match Scores for all the inner shapes; and

e) repeating d) until a Weighted Shape Match Score in the most inner shape is obtained, which represents a similarity indication between said entity of interest and said candidate entity.