Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejection – 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-5, and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kagan (US9465891B1), hereinafter referenced as Kagan, in view of Scheideler (US2019163835A1), hereinafter referenced as Scheideler.
Regarding claim 1, Kagan teaches
An industrial knowledge graph display method comprising:
“This disclosure relates to systems and methods for the visual representation and analysis of data” (¶ 2, Kagan);
determining a six-cornered grid layout for an industrial knowledge graph, wherein, a non-periphery grid is surrounded by six grids, and respective centers of the six grids form a hexagon;
“This topology may be utilized to represent a large amount of data several generations deep. Accordingly, it may be referred to as a main or overview topology, or the like. Some or all of the columns may have a hexagonal cross section. Accordingly, this topology may be referred to herein as a hex or tessellated hex.” (¶ 60, Kagan); “In general, the topologies described in this section are configured to provide an intuitive model of hierarchical data in terms of Z-height columns that are tessellatable with respect to the X-Y plane. In this example, each of the columns is hexagonal.” (¶ 80, Kagan); “In general, columns having a tessellatable cross section may themselves be tessellated, at least in terms of a two-dimensional “floor plan.” The faces or facets of neighboring columns (corresponding to the edges of the tessellatable shapes) can be placed immediately adjacent to each other similar to what is shown in FIGS. 4 and 5.” (¶ 91, Kagan)
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Kagan teaches of a hexagonal tessellation (see FIG. 4) wherein each non- periphery hex cell is mechanically surrounded by exactly six adjacent hex cells and the center of those neighbors form a hexagon.
displaying a plurality of nodes in the industrial knowledge graph at respective centers of a plurality of grids in the six-cornered grid layout; and
“In this example, each of the columns is hexagonal. Each column (or the grid location where a column is disposed) may interchangeably be referred to as a node.” (¶ 80, Kagan); “FIG. 4 shows an arrangement of six root nodes 102 , 104 , 106 , 108 , 110 , and 112 , having respective indices 1 - 6 , disposed in a contiguous circular formation, edge-to-edge, around an imaginary center point 114” (¶ 81, Kagan);
Kagan teaches of placing each node at around an imaginary center point of a grid cell within the hexagonal tessellation.
Kegan fails to teach the following: displaying a plurality of edges between the plurality of nodes based on a semantic relationship between the plurality of nodes by using at least one of the following connection lines: a straight line, a broken line, or a curve.
However, Scheideler does. Scheideler teaches:
displaying a plurality of edges between the plurality of nodes based on a semantic relationship between the plurality of nodes by using at least one of the following connection lines: a straight line, a broken line, or a curve.
“The term ‘edge’ may denote a connection or link between nodes of a knowledge graph. If nodes may typically be presented as boxes, circles and/or ellipses comprising the content inside, edges may typically be presented as lines between the nodes. A weight factor may be assigned to an edge expressing the strength of an interrelationship between the content of the related nodes.” (¶ 45, Scheideler); “As edge weights of the resulting knowledge graph, the edge of the path of the base knowledge graph is taken. The numbers for the weights are shown right beside each edge. The edges between nodes of the resulting knowledge graph are shown as bold dotted lines.” (¶ 67, Scheideler); “In a next step of the method, the resulting knowledge graph may then be converted to a graphically displayable form and presented to a user.” (¶ 76, Scheideler);
Scheideler teaches edges represent a relationship between nodes wherein each edge between each node carries semantic meaning shown as bold dotted lines.
Scheideler BASE is analogous art with respect to Kagan because they are from the same field of endeavor, namely node graph visualization. Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan with the feature of Scheideler to incorporate edges representing relationships between nodes with bold dotted lines. A person of ordinary skill in the art would do such in order to eliminate the entanglement and improve readability.
Regarding claim 2, Kagan in view of Scheideler teaches the method of claim 1, and additionally teaches the following. Kagan teaches
wherein the non-periphery grid and the six grids are all hexagonal, and a hexagon formed by the respective centers of the six grids forms an equilateral hexagon.
“In this example, each of the columns is hexagonal. Each column (or the grid location where a column is disposed) may interchangeably be referred to as a node.” (¶ 80, Kagan); “FIG. 4 shows an arrangement of six root nodes 102 , 104 , 106 , 108 , 110 , and 112 , having respective indices 1 - 6 , disposed in a contiguous circular formation, edge-to-edge, around an imaginary center point 114” (¶ 81, Kagan);
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Kagan describes a regular hex tessellation moreover, a hexagonal honeycomb arrangement, see FIG 4. All cells are hexagons of equal size arranged in a honeycomb wherein the centers of any six cells surrounding any non-periphery cell form an equilateral hexagon.
Regarding claim 3, Kagan in view of Scheideler teaches the method of claim 1, and additionally teaches the following. Kagan teaches
wherein the non-periphery grid and the six grids are all quadrilateral; and the hexagon formed by the respective centers of the six grids forms a non-equilateral hexagon.
“In general, columns having a tessellatable cross section may themselves be tessellated, at least in terms of a two-dimensional “floor plan.” The faces or facets of neighboring columns (corresponding to the edges of the tessellatable shapes) can be placed immediately adjacent to each other similar to what is shown in FIGS. 4 and 5 … In some examples, tessellatable column shapes may be arranged as if they were a different shape. For example, square cross-section columns may be represented within a hexagonal or octagonal (etc.) topology, with children extending from a parent node, for example, as if from an unoccupied edge of an imaginary hexagon shape.” (¶ 91 Kagan);
Kagan teaches arranging square cells within a hexagonal six-neighbor topology, wherein square cells are offset row-by-row in a brick pattern. The centers of the six neighbors of an interior cell form a hexagon that is not equilateral as a result of the offset quadrilateral arrangement.
Regarding claim 4, Kagan in view of Scheideler teaches the method of claim 1 wherein displaying a plurality of nodes in the industrial knowledge graph at respective centers of a plurality of grids in the six- cornered grid layout, and additionally teaches the following. Kagan teaches
placing a first node in a first grid of the plurality of grids;
“To indicate the relationship between child nodes 122 and 124, those nodes are disposed radially with respect to node 116, again in a single-file, edge-to-edge adjacency.” (¶ 83, Kagan);
Kagan teaches of placing nodes in adjacent grid cells (reads on first and second nodes in adjacent grids).
placing a second node in a second grid of the plurality of grids, wherein the second grid is adjacent to the first grid;
“Returning to the present example, additional child nodes 148 (3.1), 150 (4.1), 152 (5.1), and 154 (6.1) are shown (in phantom lines) with respect to the remaining root nodes (106, 108, 110, and 112), indicating that similar arrangements may be present for any or all of those nodes as well. As described above and shown in FIG. 4, the one or more children for any given parent node extend or protrude from one edge of the parent node in single file alignment.” (¶ 87, Kagan);
Kagan teaches of a tessellated layout in which nodes are placed in cells that are adjacent and not adjacent to each other. Like a parent node and its child node or children’s nodes of different parent root nodes separated by intervening cells.
and placing a third node in a third grid of the plurality of grids, wherein the third grid is not adjacent to the first grid or the second grid.
“FIG. 4 shows an arrangement of six root nodes 102 , 104 , 106 , 108 , 110 , and 112 , having respective indices 1 - 6 , disposed in a contiguous circular formation, edge-to-edge, around an imaginary center point 114 . Each root node represents a first-generation parent in the underlying hierarchical data set (or subset). Although a small gap is shown between node edges in FIG. 4, it should be understood that the nodes may share edges in the visualization.” (¶ 81, Kagan); “In some examples, six node positions are available, but fewer than six are occupied. In other words, fewer than six root nodes (i.e., parent categories of data) may be displayed in a six-root-node hexagonal visualization (see, e.g., FIG. 18).” (¶ 86, Kagan); “additional child nodes 148 ( 3 . 1 ), 150 ( 4 . 1 ), 152 ( 5 . 1 ), and 154 ( 6 . 1 ) are shown (in phantom lines) with respect to the remaining root nodes ( 106 , 108 , 110 , and 112 ), indicating that similar arrangements may be present for any or all of those nodes as well.” (¶ 87, Kagan);
Kagan teaches not all grid cells must be occupied. Some cells may be empty between occupied cells, indicating that a third node can be placed in a cell not adjacent to either two other nodes. The six hexagonal cells are arranged edge to edge around a central point in a continuous ring. In this arrangement each root cell shares an edge only with two immediate right neighbors and does not share an edge with three more distant root cells in the ring. Root node 106 is the first node. Child node 148 is node two. Child node 154 is the third node. Child node 154 is edge-adjacent to a different root node 112 but is not edge-adjacent to root node 106 or child node 148.
Regarding claim 5, Kagan in view of Scheideler teach the method of claim 1, and additionally teaches the following. Kagan teaches
displaying the industrial knowledge graph in a pseudo three-dimensional or three-dimensional form by skewing and rotating the six-cornered grid layout.
“The hierarchical data may be modeled as a three-dimensional object on a computing device. The model may be rotated, manipulated, and/or animated by a user.” (¶ 49, Kagan)
Claim 14 is rejected using the same rationale or bases as applied to claim 1 and the mentioned structure.
Additionally, claim 14 recites the following structure:
An electronic device comprising:
“The program code may execute entirely on a user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server.” (¶ 71, Kagan)
one or more processors; and
“These instructions are referred to as program instructions, program code, computer usable program code, or computer-readable program code that may be read and executed by a processor in processor unit 1204.” (¶ 222, Kagan);
a memory storing computer-executable instructions, wherein when executed by the one or more processors, the computer-executable instructions cause the electronic device
“The computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.” (¶ 72, Kagan); “Processor unit 1204 serves to run instructions that may be loaded into memory 1206.” (¶ 215, Kagan);
Claim(s) 6-8 and 11-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kagan, in view of the following: Scheideler, Atre (US8126926B2) hereinafter referenced as Atre, and Hagberg (NetworkX), hereinafter referenced as Hagberg.
Regarding claim 6, Kagan in view of Scheideler teaches method of claim 1, Kagan in view of Scheideler fail to teach the following: displaying the industrial knowledge graph in a global view, wherein text of at least one of the plurality of nodes and the plurality of edges is hidden; displaying the industrial knowledge graph in a local view in response to receiving a first user input for a first node of the plurality of nodes in the global view, wherein, text of at least one of a node and an edge associated with the first node is displayed; and displaying the industrial knowledge graph in a focused view in response to receiving a second user input for the first node in the local view, wherein, description information of the first node is displayed through a window.
But Atre does. Atre teaches the following:
displaying the industrial knowledge graph in a global view, wherein text of at least one of the plurality of nodes and the plurality of edges is displayed;
“A visualizer that displays data instances, such as, for example, RDF triples, constructs summary graphs that collapse a plurality of data instances into summary graphs that include summary nodes and property edges. An instance set summary graph includes at least one summary node that represents the corresponding nodes for the summarized instances. In some cases the instance set summary graph includes summary property edges. The instance set summary graph thus presents the set of instances in a summarized fashion.” (¶ 14, Atre); “Object nodes are connected to each property edge. An object node is labeled with an object value when all of the instances summarized by the instance set summary graph have the same value for that object ... Selection of an object node labeled “*” will cause the object values for the attached object node to be displayed, such as, for example, in histogram form.” (¶ 33, Atre);
Atre teaches of displaying a top-level summary graph view (reads on displaying the industrial knowledge graph in a global view) that shows the entirety of the graph instances in a collapsed/summarized form. Each object node carries text labels which can be toggled to be displayed (reads on wherein, text of at least one of a node and an edge associated with the first node is displayed).
displaying the industrial knowledge graph in a local view in response to receiving a first user input for a first node of the plurality of nodes in the global view, wherein, text of at least one of a node and an edge associated with the first node is displayed; and “While navigating the instance set summary graph, the user can select nodes or edges to expand to an instance level of granularity. The selected instance or instances are displayed in instance summary graphs that include summary nodes and edges, which in turn can be selected for expansion.” (¶ 14, Arte); “Each object node that is attached to a property edge having a count of 1 is labeled, such as “33” for the property edge “age” and “Lowell” for the property edge “residesIn”. Property edges that have a property count greater than 1, such as the “friendOf” property edge that projects from “Jack” are expandable. Selection of the property edge “friendOf” will cause the individual property edge and object nodes represented to be displayed as shown in instance summary graph E in FIG. 7 in which “Jill” and “John” nodes are displayed.” (¶ 39, Atre); “the graph navigator allows the selection of a plurality of subject nodes to be replaced by the summary subject node as seen in FIG. 5 instance set summary graph C. In one example embodiment, the graph navigator is configured to allow selection of a property edge. Selection of the property edge causes the object values for the selected property edge to be displayed. In one example embodiment, graph navigator 410 is configured to allow selection of a subject value for one of the subject nodes replaced by the summary subject node as seen in FIG. 6 instance summary graph D. The selected subject node having the selected subject value is substituted for the summary subject node. In this manner, the instance summary graph is constructed that depicts the selected subject node and properties connected to the selected subject node.” (¶ 52-53; Atre);
Atre teaches in response to a user node selection in the global summary view (reads on displaying the industrial knowledge graph in a local view in response to receiving a first user input for a first node of the plurality of nodes in the global view), the view expands to an instance level of granularity. This a second-tier instance summary graph view shows the selected node expanded with its associated edges and adjacent nodes (reads on wherein, text of at least one of a node and an edge associated with the first node is displayed)
displaying the industrial knowledge graph in a focused view in response to receiving a second user input for the first node in the local view, wherein, description information of the first node is displayed through a window.
“The selected instance or instances are displayed in instance summary graphs that include summary nodes and edges, which in turn can be selected for expansion.” (¶ 14, Atre); “Each object node that is attached to a property edge having a count of 1 is labeled, such as “33” for the property edge “age” and “Lowell” for the property edge “residesIn”. Property edges that have a property count greater than 1, such as the “friendOf” property edge that projects from “Jack” are expandable. Selection of the property edge “friendOf” will cause the individual property edge and object nodes represented to be displayed as shown in instance summary graph E in FIG. 7 in which “Jill” and “John” nodes are displayed.” (¶ 39, Arte); “The computing system 300 includes a display 330 that displays the instance set summary graph.” (¶ 44, Atre);
Atre teaches of a three-tier navigation system which includes a summary graph, instance summary graph, and further expanded detail view. Each transition between tier is driven by user selection and input When a user selects an edge or node within the second-tier instance summary graph (reads on displaying the industrial knowledge graph in a focused view in response to receiving a second user input for the first node in the local view) the system to display fully detailed nodes with their individual descriptive labels displayed on a display 330 (description information of the first node is displayed through a window).
Atre BASE is analogous art with respect to Kagan in view of Scheideler because they are from the same field of endeavor, namely data visualization. Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler with the feature of Atre to incorporate a hierarchical, multi-view user interface for navigating complex, data-rich diagrams which includes a global view, a local view, and a focused view. A person of ordinary skill in the art would do such in order to improve data visualization and organization.
Kagan in view of Scheideler and Atre fail to teach a view wherein text of at least one of the plurality of nodes and the plurality of edges is hidden.
But Hagberg does. Hagberg teaches a teach a view wherein text of at least one of the plurality of nodes and the plurality of edges is hidden.
“restricted_view(G, nodes, edges) Returns a view of G with hidden nodes and edges.The resulting subgraph filters out node nodes and edges edges. Filtered out nodes also filter out any of their edges.” (Section Function > restricted_view, Hagberg); “A NodeView of the Graph as G.nodes or G.nodes().Can be used as G.nodes for data lookup and for set-like operations. Can also be used as G.nodes(data='color', default=None) to return a NodeDataView which reports specific node data but no set operations. Parameters: data : string or bool, optional (default=False) The node attribute returned in 2-tuple (n, ddict[data]). If True, return entire node attribute dict as (n, ddict). If False, return just the nodes n. default : value, optional (default=None) Value used for nodes that don’t have the requested attribute. Only relevant if data is not True or False.” (Section Graph types > Graph—Undirected graphs with self > loops > Graph.nodes, Hagberg);
Hagberg teaches of a restricted_view in which nodes and edges are filtered out (reads on wherein text of at least one of the plurality of nodes and the plurality of edges is hidden). Each node consists of data and default parameters (text of at least one of the plurality of nodes). When a node is filtered out so is its parameters. (reads on text of at least one of the pluralities of is hidden).
Hagberg is analogous art with respect to Kagan in view of Scheideler and Atre because they are from the same field of endeavor, namely data visualization via graphs. Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler and Atre with the feature of Hagberg to incorporate a view wherein text of at least one of the plurality of nodes and the plurality of edges is hidden a view wherein text of at least one of the plurality of nodes and the plurality of edges is hidden. A person of ordinary skill in the art would do such in order to improve graph readability and use.
Regarding claim 7, Kagan in view of Scheideler, Atre, and Hagberg teach method of claim 6, and additionally teaches the following. Kagan teaches
displaying the industrial knowledge graph in the local view in response to receiving a third user input a view
“3-D renderings may be interactive, such that a user can manipulate the view through the user interface, e.g., by panning, rotating, zooming, selecting, and/or the like” (¶ 52, Kagan); “As mentioned above, several interactive topologies may be used to display a selected portion (or all) of the data. Each of the following visualization topologies is described briefly here as an overview, and described in further detail below along with other topologies and examples.” (¶ 59, Kagan);
Kagan teaches of displaying an interactive industrial knowledge graph which zooms in and out via user input on the graphical user interface.
Atre teaches the following:
displaying the industrial knowledge graph in the local view in response to receiving a third user input in the focused view
“Thus a graph is created that contains details of some parts, and summaries of other parts, thereby creating a “fish eye” view.” (¶ 15, Atre); “The graph navigator 410 thus allows a user to select nodes and edges for summarization and expansion to create a custom graphical display with portions that represent summarized data and other portions that represent un-summarized data.” (¶ 54, Atre);
Atre traches that the graph navigator supports both moving towards detail and collapsing back towards summary. The user can issue a summarization input that collapses an expanded detail back (reads on the industrial knowledge graph in the local view in response to receiving a third user input in the focused view) The user can move between the summarized and detailed representation of any node allowing the user to its collapse the focused detail of a node back to its summary representation.
displaying the industrial knowledge graph in the global view in response to receiving a fourth user input in the local view.
“An instance set summary graph includes at least one summary node that represents the corresponding nodes for the summarized instances. In some cases the instance set summary graph includes summary property edges. The instance set summary graph thus presents the set of instances in a summarized fashion. While navigating the instance set summary graph, the user can select nodes or edges to expand to an instance level of granularity. The selected instance or instances are displayed in instance summary graphs that include summary nodes and edges, which in turn can be selected for expansion.” (¶ 14, Atre); “The graph navigator 410 thus allows a user to select nodes and edges for summarization and expansion to create a custom graphical display with portions that represent summarized data and other portions that represent un-summarized data.” (¶ 54, Atre);
Atre teaches user input driven summarization which collapses the instance summary representation back into the summary graph representation (reads on the industrial knowledge graph in the global view in response to receiving a fourth user input in the local view)
Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler, Atre, and Hagberg with the feature of Atre to summarization to collapse and expand the instance summary representation back into the summary graph representation and vice versa. A person of ordinary skill in the art would do such in order to improve data visualization, organization, and readability.
Regarding claim 8, Kagan in view of Scheideler, Atre, and Hagberg teaches method of claim 7, and additionally teaches the following. Kagan briefly teaches the following
displaying the industrial knowledge graph in the focused view in response to receiving a fifth user input for the first node in the global view; and
“While navigating the instance set summary graph, the user can select nodes or edges to expand to an instance level of granularity. The selected instance or instances are displayed in instance summary graphs that include summary nodes and edges, which in turn can be selected for expansion.” (¶ 14, Atre); “The dynamic subset visualizer 370 includes a summary subject node selector 380 that selects a summary node for the instance set summary graph based on the query. The dynamic subset visualizer transforms the results to a user query into an instance set summary graph. The summary subject node selector selects a summary subject node by augmenting a user query that specifies a focal point with a group by command on the focal point. This results in a focused instance set summary graph that efficiently displays the query results and can be computed with an interactive response time.” (¶ 50, Atre); “the graph navigator is configured to allow selection of an object node. Selection of the object node causes property values and objects for the selected object node to be displayed. Hence the graph navigator generates a node summary graph about the selected object node.” (¶ 53, Atre);
Atre traches that a user node selection in the summary view expands directly with no intermediate stop. The user can select either a node or an edge in the summary view (reads on global view) to drive expansion to the instance detail level (reads on the focused view). This directly causes the property values and object for the selected node to be displayed.
displaying the industrial knowledge graph in the global view in response to receiving a sixth user input in the focused view.
“An instance visualizer 320 constructs an instance set summary graph that represents a subset of instances in the instance store. As described above, the instance set summary graph includes at least one summary subject node having at least one property edge that connects the summary subject node to an object node. Each summary subject node represents the subject values for a set of instances summarized by the summary subject node. The computing system 300 includes a display 330 that displays the instance set summary graph.” (¶ 54, Atre); “The graph navigator 410 thus allows a user to select nodes and edges for summarization and expansion to create a custom graphical display with portions that represent summarized data and other portions that represent un-summarized data.” (¶ 54, Arte);
Arte teaches that the summary graph is the displayed default representation of the dataset in which the user can return to from any expanded view via the summarization function (reads on displaying the industrial knowledge graph in the global view in response to receiving a sixth user input in the focused view). The user driven graph navigator collapses any expanded portion of the display back into its summary representation.
Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler, Atre, and Hagberg with the feature of Atre to incorporate a dynamic, interactive user interface wherein a user navigates between two viewing modes of an industrial data system. A person of ordinary skill in the art would do such in order to improve data visualization.
Regarding claim 11, Kagan in view of Scheideler, Atre, and Hagberg teaches method of claim 6 wherein displaying the industrial knowledge graph in a local view, and additionally teaches the following. Kagan teaches
displaying the first group of related nodes and text thereof in the local view.
“Drilling down may allow a user to gain more detailed information about a data set, see how data evolves over time, see how relationships between data elements evolve over time, and/or any other appropriate analysis of the underlying data' Drilling down may allow a user to gain more detailed information about a data set, see how data evolves over time, see how relationships between data elements evolve over time, and/or any other appropriate analysis of the underlying data” (¶ 110, Kagan)
Kagan teaches of a drill-down view (reads on local view) that displays the selected node’s related nodes and its text.
Scheideler teaches:
determining a first group of related nodes within a predetermined numbers of hops of the first node; and
“a pre-determined clip level (i.e., threshold) may be applied, for example, the search for links can be stored after a certain length of the path (e.g. number of edges) or after a certain accumulative inverse weight (e.g. some of the inverse weights of the links of the path) has been reached. The edges between the super-imposed, hexagonal incoherent nodes are shown as bold double lines. A clip level may be set to four edges of the base knowledge graph.” (¶ 56, Scheideler); “a weight of a new edge between two of the new nodes may be determined by a count of edges forming a shortest connection between the two corresponding nodes of the existing knowledge graph. Thus, also newly built edges of the to-be-created knowledge graph may have weights. There may be different options for assigning weights to the newly created edges, which may also reflect the organization of the base knowledge graph.” (¶ 31, Scheideler);
Scheideler teaches of a predetermined clip level (reads on predetermined numbers of hops) defined as a number of edges to determine which related nodes are connected to a given node within that path length (reads on a first group of related nodes within a predetermined numbers of hops of the first node).
Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler, Atre, and Hagberg with the feature of Scheideler to incorporate a predetermined clip level to determine which related nodes are connected to a given node within that path length. A person of ordinary skill in the art would do such in order to improve knowledge graph organization and visualization.
Regarding claim 12, Kagan in view of Scheideler, Atre, and Hagberg teaches method of claim 11 wherein the displaying the industrial knowledge graph in a local view, and additionally teaches the following. Atre teaches
in response to receiving selection for a second node in the local view, displaying the second group of related nodes and text thereof in the local view,
“While navigating the instance set summary graph, the user can select nodes or edges to expand to an instance level of granularity. The selected instance or instances are displayed in instance summary graphs that include summary nodes and edges, which in turn can be selected for expansion.” (¶ 14, Atre); “graph navigator 410 is configured to allow selection of a subject value for one of the subject nodes replaced by the summary subject node as seen in FIG. 6 instance summary graph D. The selected subject node having the selected subject value is substituted for the summary subject node. In this manner, the instance summary graph is constructed that depicts the selected subject node and properties connected to the selected subject node.” (¶ 53, Atre);
Atre the view displays more data and information in response to user selection of nodes and edges (reads on in response to receiving selection for a second node in the local view, and displaying the second group of related nodes and text thereof in the local view). The graph navigator receives a user selection of a new subject node within the current display and in response to the selection, constructs a new view in which the newly selected node is now the focal node and its connected properties.
Scheideler teaches:
In response a system path-search operation between two nodes, determining a second group of related nodes within a pr determined hops of the second node;
“a pre-determined clip level (i.e., threshold) may be applied, for example, the search for links can be stored after a certain length of the path (e.g. number of edges) or after a certain accumulative inverse weight (e.g. some of the inverse weights of the links of the path) has been reached. The edges between the super-imposed, hexagonal incoherent nodes are shown as bold double lines. A clip level may be set to four edges of the base knowledge graph.” (¶ 56, Scheideler)
Scheideler teaches the clip-level threshold is applied around whichever node in response to the system preforming a path-search operation between two nodes.
Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler, Atre, and Hagberg, and Scheideler with the feature of Scheideler and Atre to incorporate clip-level threshold application when node is selected as the focal node in response to user selection of nodes and edges wherein based on the user selection of a new subject node a new view in which the newly selected node is now the focal node and its connected properties A person of ordinary skill in the art would do such in order to improve data visualization.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kagan in view of the following: Scheideler, Atre, Hagberg, Graphviz (Node Shapes), hereinafter referenced as Graphviz.
Regarding claim 9, Kagan in view of Scheideler, Atre, and Hagberg teaches method of claim 6 wherein the displaying the industrial knowledge graph in a global view, and additionally teaches the following. Kagan teaches
displaying a first-type node in the plurality of nodes as a first icon;
“Moreover, each node may include corresponding indicia, which may be selected to show a category name, an index value, date-related information, magnitude, and/or the like, or any combination of these.” (¶ 89, Kagan);
Kagan fails to teach displaying a second-type node in the plurality of nodes as a second icon different from the first icon.
But Kagan in view of Scheideler, Atre, and Hagberg fail to teach the following: and displaying a second-type node in the plurality of nodes as a second icon different from the first icon.
“There are three main types of shapes: polygon-based, record-based and user-defined.” (Graphviz)
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Graphviz teaches nodes of different shape, icons, and colors.
Graphviz BASE is analogous art with respect to Kagan in view of Scheideler, Atre, and Hagberg because they are from the same field of endeavor, namely data visualization using graphs. Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler, Atre, and Hagberg with the feature of Graphviz to incorporate nodes of different shape, icons, and colors. A person of ordinary skill in the art would do such in order to improve data visualization.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kagan in view of the following: Scheideler, Atre, Hagberg, Natali (Graph-based representations of point clouds), hereinafter referenced as Graph-based representations of point clouds.
Regarding claim 10, Kagan in view of Scheideler, Atre, and Hagberg teaches method of claim 6 wherein the displaying the industrial knowledge graph in a global view, and Scheideler teaches the following:
aggregating the plurality of nodes into a plurality of groups; and
“clusters of incoherent nodes can be identified to sort the incoherent nodes into categories and name a topic or a theme for each category. For this purpose, all nodes get as a score the sum of the weights of the edges. In another exemplary embodiment, the nodes get as a score the number of edges.” (¶ 62, Scheideler);
Scheideler teaches aggregating graph nodes into clusters based on edge-weight scoring (reads on aggregating the plurality of nodes into a plurality of groups).
displaying the plurality of groups in the global view.
“The clustering engine 918 identifies the scores of the clusters, picks a name string from the node name and assigned surrounding nodes of the cluster to the cluster. The presentation module 920 then renders one or more graphics depicting clusters, nodes and links of the resulting knowledge graph 912. The user interface 922 allows the user to alter power meters of the clustering algorithm to generate different views of the resulting knowledge graph 912.” (¶ 80-81, Scheideler);
Scheideler teaches rendering the clustered groups graphically in the displayed knowledge graph. (reads on displaying the plurality of groups in the global view)
Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler, Atre, and Hagberg with the feature of Scheideler to aggregating graph nodes into clusters based on edge-weight scoring and render such clustered groups graphically in the displayed knowledge graph. A person of ordinary skill in the art would do such in order to improve graph readability and clarity.
Kagan in view of Scheideler, Atre, and Hagberg fail to teach the global view in a point cloud manner.
But Natali does. Natali teaches the following:
a graph view in a point cloud manner
“This paper introduces a skeletal representation, called Point Cloud Graph, that generalizes the definition of the Reeb graph to arbitrary point clouds sampled from m-dimensional manifolds embedded in the d-dimensional space. The proposed algorithm is easy to implement and the graph representation yields to an effective abstraction of the data. Finally, we present experimental results on point-sampled surfaces and volumetric data that show the robustness of the Point Cloud Graph to non-uniform point distributions and its usefulness for shape comparison” (Abstract, Natali).
Natali teaches of a skeletal representation, called Point Cloud Graph to represent graphs.
Natali BASE is analogous art with respect to Kagan in view of Scheideler, Atre, and Hagberg, Hagberg, and Scheideler because they are from the same field of endeavor, namely data visualization via graphs. Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler, Atre, and Hagberg, and Scheideler with the feature of Natali to include a graph view in a point cloud manner. A person of ordinary skill in the art would do such in order to improve data visualization.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kagan in view of the following: Scheideler, Atre, Hagberg, in view of Shneiderman (The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations), hereinafter referenced as Shneiderman.
Regarding claim 13, Kagan in view of Scheideler, Atre, and Hagberg teaches method of claim 6 wherein displaying the industrial knowledge graph in a focused view, and additionally teaches the following. Kagan briefly teaches
nodes with color scheme
“each set of child nodes may share a common color scheme, allowing visual separation and grouping.” (¶ 89, Kagan);
Kagan teaches of visual emphasis of node sets via color coding.
Kagan in view of Scheideler, Atre, and Hagberg fail to directly teach highlighting the first node compared with another displayed node in the focused view.
However, Shneiderman does. Shneiderman teaches:
highlighting the first node compared with another displayed node in the focused view.
“Similarly, in SDM (Chuah et al., 1995), users can select an item and then highlight items with similar attributes or in LifeLines (Plaisant et al., 1996) users can click on a medication and see the related visit report, prescription, and lab test…Highlighting techniques (for example, bold-face text or brightening, inverse video, blinking, underscoring, or boxing) can be used to draw attention to certain items in a field of thousands of items. Pointing to a visual display can allow rapid selection, and feedback is apparent. The eye, the hand, and the mind seem to work smoothly and rapidly as users perform actions on visual displays.” (Page 5, Shneiderman);
Shneiderman teaches highlighting techniques to draw attention to selected items (reads on highlighting the first node compared with another displayed node in the focused view).
Shneiderman is analogous art with respect to Kagan in view of Scheideler, Atre, and Hagberg because they are from the same field of endeavor, namely data organization. Before the effective filling date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to modify Kagan in view of Scheideler, Atre, and Hagberg, and Scheideler with the feature of Shneiderman to incorporate highlighting techniques to draw attention to selected items. A person of ordinary skill in the art would do such in order to improve data visualization.
Conclusion
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/DUNE NGOC NGUYEN/Examiner, Art Unit 2618
/DEVONA E FAULK/Supervisory Patent Examiner, Art Unit 2618
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