DETAILED ACTION
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 4/08/2026 has been entered.
Claim Rejections - 35 USC § 103
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) 1-4, 10-13, 15-18 and 24-27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kanza et al. (US PGPUB No. 2018/0006898; Pub. Date: Jan. 4, 2018) in view of VANGALA et al. (US PGPUB No. 2021/0026859; Pub. Date: Jan. 28, 2021).
Regarding independent claim 1,
Kanza discloses a computer-implemented method for querying infrastructure information, the method comprising: executing instructions stored on a non-transitory computer-readable storage medium and, when the instructions are executed by one or more processors, cause the one or more processors to perform operations comprising:(a) receiving an input query from a user to query about an object in an infrastructure, See Paragraphs [0031]-[0032], (Disclosing a system comprising a graph database configured to return a pathway set representing elements of a network in response to a query. The system may build a network inventory of a communication network based on a schema that supports querying via a query language and may include supporting Topology and Orchestration Specification for Cloud Applications (TOSCA) abstractions. The TOSCA model may utilize hierarchies to facilitate querying networks in cases where a user only has partial information regarding the types of nodes or edges in the network.) See Paragraph [0034], (An input 212 comprising query instructions may be received and applied to graph database 210 in order to produce a set of pathways which are outputted as query results, i.e. a computer-implemented method for querying infrastructure information, the method comprising: executing instructions stored on a non-transitory computer-readable storage medium and, when the instructions are executed by one or more processors, cause the one or more processors to perform operations comprising:(a) receiving an input query from a user to query about an object in an infrastructure (e.g. users may query a network inventory of a communication network 100 using a TOSCA model).)
wherein the infrastructure comprises a plurality of physical and virtual resources defined in a graphical schema, See Paragraph [0058], (The network inventory is associated with a graphical representation comprising nodes and edges, i.e. wherein the infrastructure comprises a plurality of physical and virtual resources defined in a graphical schema. Note [0029] wherein network 100 includes network entities associated with virtual network functions, i.e. virtual resources, and may additionally include physical hardware 110 such as a hypervisor host 110a, i.e. physical resources.)
wherein the virtual resources comprise at least a resource provided via virtualization technology for cloud native applications; See Paragraph [0029], (Network 100 may include network entities including virtual network functions such as a firewall, DNS, VNF, web service, etc.) See Paragraph [0031], (The system may build a network inventory of a communication network based on a schema that supports querying via a query language and may include supporting Topology and Orchestration Specification for Cloud Applications (TOSCA) abstractions, i.e. wherein the virtual resources comprise at least a resource provided via virtualization technology for cloud native applications (e.g. network 100 includes a plurality of virtual network functions that may be represented in a network inventory that may be queried using query languages that support cloud application abstractions).)
(b) upon receiving the input query, traversing the graphical schema to i) identify one or more resources from the plurality of physical and virtual resources that are connected to the object, See Paragraph [0097], (A query may use or identify induced pathways defined by a query element to facilitate traversal of the graph database representing network100, such as a vertical traversal to move between layers or a horizontal traversal in order to determine node matches that correspond to query elements, i.e. upon receiving the input query, traversing the graphical schema to i) identify one or more resources from the plurality of physical and virtual resources that are connected to the object (e.g. Note [0029] wherein network 100 comprises virtual elements as well as physical hardware which are represented as elements of the graph as in FIG. 1B.)
and ii) collect information about a relationship between the object and the one or more resources, See FIG. 2C, (FIG. 2C illustrates method 250 comprising step 255 of receiving a query for a graph database, the query including pathway variables. At step 275, the method executes a pathway algebraic expression generated based on pathway variables of the query in order to return a pathway set.) See Paragraph [0077], (A query may retrieve edges wherein an edge may comprise a pathway . Note [0044] wherein an edge indicates a connection between at least two nodes, i.e. and ii) collect information about a relationship between the object and the one or more resources (e.g. a query may retrieve an edge which represents connection data associated with a plurality of nodes).)
Kanza does not disclose the step of and ii) collect information about a relationship between the object and the one or more resources, wherein the one or more resources and the relationship between the object and the one or more resources are identified by the traversing without being specified in the input query, and in response to the input query, scanning the graphical schema for collecting real-time metadata about the one or more resources or the object;
and(c) aggregating the information about the relationship and the metadata to construct a result for display in response to the input query, wherein the result comprises at least information not queried in the input query.
VANGALA discloses the step of ii) collect information about a relationship between the object and the one or more resources, wherein the one or more resources and the relationship between the object and the one or more resources are identified by the traversing without being specified in the input query, and in response to the input query, See Paragraph [0046], (Disclosing a system for extracting user data items from a collection of one or more applications sources. Interaction component 124 allows different applications to interrogate a graph 104 to identify an initial set of nodes that match a query specified by a user. Interaction component 124 may then expand the initial set of nodes to identify additional nodes to determine a subgraph that includes the initial set of nodes and additional nodes. Note [0032] wherein graph 103 is constructed based on data items received from one or more data sources 106 associated with application sources 108. The expansion process comprises following links that emanate from initial nodes to the additional nodes based on a specified degree of relationship, i.e. ii) collect information about a relationship between the object and the one or more resources (e.g. interaction component 124 may identify nodes responsive to a query and identify additional nodes based on a degree of relationship between them), wherein the one or more resources and the relationship between the object and the one or more resources are identified by the traversing without being specified in the input query, and in response to the input query (e.g. the identified additional nodes are determined after determining an initial set of nodes that is directly responsive to the query),
scanning the graphical schema for collecting real-time metadata about the one or more resources or the object; See Paragraph [0005], (The disclosed search process comprises a plurality of phases including an application phase that allows a user to interrogate a relational data structure by submitting a query to an interaction component to identify an initials et of objects that match the query. Note the Abstract wherein the process of interrogating a data source is performed in real-time.) See Paragraph [0031], (Users may direct queries to a relational data structure represented as a graph including objects represented as nodes connected by edges describing relationships among objects, i.e. scanning the graphical schema for collecting real-time metadata about the one or more resources or the object (e.g. the interrogation process of identifying nodes is performed in real-time by searching a graph structure);)
and(c) aggregating the information about the relationship and the metadata to construct a result for display in response to the input query, wherein the result comprises at least information not queried in the input query. See Paragraph [0101], (FIG. 10 illustrates the process of applying the relational data structure comprising step 1004 of receiving a question in response to interaction by a user with an input device. At step 1014, the filtered output result is transmitted to an output device. Note [0007] wherein the process aggregates information from different sources to construct an output) See Paragraph [0071], (Nodes of a graph data structure comprise metadata describing a node such as by establishing implicit links between nodes without allocating a separate data construct to describe each relation. Metadata may include location data and time data, i.e. (c) aggregating the information about the relationship and the metadata to construct a result for display (e.g. node attributes including metadata and edge information is used to identify objects responsive to a query) in response to the input query, wherein the result comprises at least information not queried in the input query (e.g. the output results include additional nodes identified during the expansion process of [0046]).
Kanza and VANGALA are analogous art because they are in the same field of endeavor, search systems. It would have been obvious to anyone having ordinary skill in the art before the effective filing date to modify the system of Kanza to include the method of performing expanded searches as disclosed by VANGALA. Paragraph [0007] of VANGALA discloses that the system allows users to retrieve information efficiently by separately interrogating separate sources without requiring explicit user input identifying each potential data source.
Regarding dependent claim 2,
As discussed above with claim 1, Kanza-VANGALA discloses all of the limitations.
VANGALA further discloses the step wherein the input query is an unstructured text query or in natural language. See Paragraph [0086], (Search component 602 may receive user input queries comprising search terms. For example, a user may submit the name "John Brown" and a user's specification of a "contact" node type to perform a search, i.e. wherein the input query is an unstructured text query or in natural language (e.g. the user input includes text such as specifying a name).)
Regarding dependent claim 10,
As discussed above with claim 1, Kanza-VANGALA discloses all of the limitations.
Kanza further discloses the step wherein each resource of the infrastructure is represented as a node in the graphical schema. See Paragraph [0022], (The schema of the layered network graph may comprises nodes and edges having a plurality of types. Note FIG. 1B wherein a plurality of nodes are arranged as part of a layered graph wherein the nodes represent elements of network 100, i.e. wherein each resource of the infrastructure is represented as a node in the graphical schema.)
Regarding dependent claim 11,
As discussed above with claim 1, Kanza-VANGALA discloses all of the limitations.
VANGALA further discloses the step wherein the metadata of the object is represented as a node in the graphical schema. See Paragraph [0071], (Nodes in graph 104 may include metadata that establishes implicit links between nodes, i.e. wherein the metadata of the object is represented as a node in the graphical schema (e.g. node metadata affects the structure of nodes and edges in graph 104).)
Regarding dependent claim 12,
As discussed above with claim 1, Kanza-VANGALA discloses all of the limitations.
Kanza further discloses the method further comprising updating the graphical schema upon detection of a change in the infrastructure. See Paragraph [0049], (The system may receive an input 202 indicating an update describing a change in network 100’s structure such as the addition of a new node or edge, i.e. updating the graphical schema upon detection of a change in the infrastructure.)
Regarding dependent claim 13,
As discussed above with claim 1, Kanza-VANGALA discloses all of the limitations.
VANGALA further discloses the step wherein the at least information not queried in the input query comprises information about the relationship between the object and the one or more resources. See Paragraph [0046], (The method may expand an initials et of nods to identify additional nodes based on links that indicate a degree of relationship between nodes of the graph, i.e. wherein the at least information not queried in the input query comprises information about the relationship between the object and the one or more resources (e.g. the initial set of nodes is determined based on the input query, the additional nodes are determined by the expansion operation).)
Regarding independent claim 15,
The claim is analogous to the subject matter of independent claim 1 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 16,
The claim is analogous to the subject matter of dependent claim 2 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 24,
The claim is analogous to the subject matter of dependent claim 10 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 25,
The claim is analogous to the subject matter of dependent claim 11 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 26,
The claim is analogous to the subject matter of dependent claim 12 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 27,
The claim is analogous to the subject matter of dependent claim 13 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Claim(s) 3-8 and 17-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kanza in view of VANGALA as applied to claim 2 above, and further in view of Pal et al. (US PGPUB No. 2019/0147084; Pub. Date: May 16, 2019).
Regarding dependent claim 3,
As discussed above with claim 2, Kanza-VANGALA discloses all of the limitations.
Kanza-VANGALA does not disclose the step wherein the input query is processed and converted into one or more executable query codes.
Pal discloses the step wherein the input query is processed and converted into one or more executable query codes. See Paragraph [0077], (Disclosing a system for executing a query including an indication to process data managed by an external system. Search process master 3302 may parse an incoming query and allocate the query to a particular query coordinator for execution and spawn an additional query coordinator 3304 to execute the query, i.e. wherein the input query is processed and converted into one or more executable query codes. Note [0762] wherein query coordinator 3304 may break up a query or subquery into multiple parts and assign each part for execution, i.e. wherein the input query is processed and converted into one or more executable query codes.)
Kanza, VANGALA and Pal are analogous art because they are in the same field of endeavor, graph-based data retrieval. It would have been obvious to anyone having ordinary skill in the art before the effective filing date to modify the system of Kanza-VANGALA to include the method of performing partial computations on requested data as disclosed by Pal. Paragraph [0244] of Pal discloses that the process allows the search head to start returning interim results to the user at the client device. Paragraph [0353] also discloses that search head 210 allows users to search and visualize events generated from machine data received form homogeneous data sources.
Regarding dependent claim 4,
As discussed above with claim 3, Kanza-VANGALA-Pal discloses all of the limitations.
Pal further discloses the step wherein the one or more executable query codes are delivered to one or more distributed agents at the one or more resources. See FIG. 6A & Paragraph [0333], (FIG. 6A illustrates the search method comprising step 602 of receiving a query from a client followed by step 604 of determining which portions of the query can be distributed to indexers for execution, i.e. wherein the one or more executable query codes are delivered to one or more distributed agents at the one or more resources.)
Regarding dependent claim 5,
As discussed above with claim 4, Kanza-VANGALA-Pal discloses all of the limitations.
Pal further discloses the step wherein the method further comprising executing the one or more executable query codes to collect the metadata from the one or more resources and combining the data as the result of the input query. See Paragraph [0271], (Disclosing a system for executing a query including an indication to process data managed by an external system. The system comprises a plurality of indexers configured to return partial responses to a search head that combines the results to produce an answer for the query, i.e. executing the one or more executable query codes (e.g. the subqueries) to collect the data from the one or more resources (e.g. retrieving partial responses) and combining the data as a result of the input query (e.g. the search head combines the partial responses).) Note [0956] wherein the search process includes a comparison of metadata associated with messages received during a given time-window in order to identify any messages not relevant to a given query, i.e. collecting metadata from one or more resources.
Regarding dependent claim 6,
As discussed above with claim 3, Kanza-VANGALA-Pal discloses all of the limitations.
Pal further discloses the step wherein the one or more executable query codes are executed in parallel. See Paragraph [0271], (Each indexer may analyze events for a query in parallel to determine partial responses to a query that are later combined to produce an answer for the query, i.e. wherein the one or more executable query codes are executed in parallel.)
Kanza, VANGALA and Pal are analogous art because they are in the same field of endeavor, graph-based data retrieval. It would have been obvious to anyone having ordinary skill in the art before the effective filing date to modify the system of Kanza-VANGALA to include the method of performing partial computations on requested data as disclosed by Pal. Paragraph [0244] of Pal discloses that the process allows the search head to start returning interim results to the user at the client device. Paragraph [0353] also discloses that search head 210 allows users to search and visualize events generated from machine data received form homogeneous data sources.
Regarding dependent claim 7,
As discussed above with claim 3, Kanza-VANGALA discloses all of the limitations.
Kanza-VANGALA does not disclose the step wherein the one or more executable codes are expressed in distributed data query language which comprises at least a building block for filtering and extracting data with an assertion feature.
Pal further discloses the step wherein the one or more executable codes are expressed in distributed data query language which comprises at least a building block for filtering and extracting data with an assertion feature. See Paragraph [0344]-[0345], (Commands may be used to filter unwanted information out of results by retrieving a set of data based on a condition, i.e. wherein the one or more executable codes are expressed in distributed data query language (e.g. Note [0338] wherein a query coordinator may generate subqueries to be executed by indexers) which comprises at least a building block for filtering. Queries may include search terms that can include any combination of keywords, phrases, times, dates, Boolean expressions, etc., i.e. an assertion feature.)
Kanza, VANGALA and Pal are analogous art because they are in the same field of endeavor, graph-based data retrieval. It would have been obvious to anyone having ordinary skill in the art before the effective filing date to modify the system of Kanza-VANGALA to include the method of performing partial computations on requested data as disclosed by Pal. Paragraph [0244] of Pal discloses that the process allows the search head to start returning interim results to the user at the client device. Paragraph [0353] also discloses that search head 210 allows users to search and visualize events generated from machine data received form homogeneous data sources.
Regarding dependent claim 8,
As discussed above with claim 7, Kanza-VANGALA-Pal discloses all of the limitations.
Pal further discloses the step wherein the distributed data query language further comprises a scripting building block and data query building block. See Paragraph [0344]-[0345], (Queries may comprise search commands and one or more corresponding search terms, i.e. a data query building block. Commands may be used to filter unwanted information, extract more information, evaluate field values, calculate statistics, reorder results, create summaries/alerts, etc., i.e. a scripting building block.)
Paragraph [0033] of Applicant's specification defines a "scripting feature" as a programming language that executes a task or set of tasks. Additionally, Paragraph [0034] of Applicant's specification defines a "data query building block" as being used to retrieve information or fetch data related to a resource. Therefore, one of ordinary skill in the art would recognize that a "scripting building block" comprises a query command that performs an operation. Similarly, one of ordinary skill int he art would recognize that a search command directed to search terms would be equivalent to the "data query building block" as described in Applicant's Specification.
Kanza, VANGALA and Pal are analogous art because they are in the same field of endeavor, graph-based data retrieval. It would have been obvious to anyone having ordinary skill in the art before the effective filing date to modify the system of Kanza-VANGALA to include the method of performing partial computations on requested data as disclosed by Pal. Paragraph [0244] of Pal discloses that the process allows the search head to start returning interim results to the user at the client device. Paragraph [0353] also discloses that search head 210 allows users to search and visualize events generated from machine data received form homogeneous data sources.
Regarding dependent claim 17,
The claim is analogous to the subject matter of dependent claim 3 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 18,
The claim is analogous to the subject matter of dependent claim 4 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 19,
The claim is analogous to the subject matter of dependent claim 5 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 20,
The claim is analogous to the subject matter of dependent claim 6 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 21,
The claim is analogous to the subject matter of dependent claim 7 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Regarding dependent claim 22,
The claim is analogous to the subject matter of dependent claim 8 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Claim(s) 14 and 28 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kanza in view of VANGALA as applied to claim 1 above, and further in view of Khillar et al. (US PGPUB No. 2021/0026898; Pub. Date: Jan. 28, 2021).
Regarding dependent claim 14,
As discussed above with claim 1, Kanza-VANGALA discloses all of the limitations.
Kanza-VANGALA does not disclose the method further comprising automatically completing the input query by displaying available one or more resources on a user interface.
Khillar discloses a method comprising automatically completing the input query by displaying available one or more resources on a user interface. See Paragraph [0060], (Disclosing a system for generation of a database schema-compliant search query based on a natural language input. Client 301 may auto-complete the user search query based on segments of the database schema, i.e. automatically completing the input query by displaying available one or more resources on a user interface (e.g. Note [0080] wherein search query recommendations may aid the user in typing elements of the search input query of a graphical user interface).)
Kanza, VANGALA and Khillar are analogous art because they are in the same field of endeavor, natural language query systems. It would have been obvious to anyone having ordinary skill in the art before the effective filing date to modify the system of Kanza-VANGALA to include the method for auto-completing user queries according to database information as disclosed by Khillar. Paragraph [0060] of Khillar discloses that the recommendation algorithm associated with the auto-complete functionality may advantageously enhance the accuracy of the natural language input by potentially avoiding misspellings of column titles of a database table.
Regarding dependent claim 28,
The claim is analogous to the subject matter of dependent claim 14 directed to a non-transitory, computer readable medium and is rejected under similar rationale.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1 and 15 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant’s amendments necessitated the new grounds of rejection presented in this Office Action.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Fernando M Mari whose telephone number is (571)272-2498. The examiner can normally be reached Monday-Friday 7am-4pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ann J. Lo can be reached at (571) 272-9767. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/FMMV/Examiner, Art Unit 2159
/ANN J LO/Supervisory Patent Examiner, Art Unit 2159
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