/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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 November 14, 2025 has been entered.
In response to Applicant’s claims filed on November 14, 2025, claims 11-27 are now pending for examination in the application.
Information Disclosure Statement
The information disclosure statements (IDS) filed on 12/16/24 has been considered by the Examiner and made of record in the application file.
Claim Objections
Claim20 is objected to because of the following informalities: Claim 20 is directed toward the electronic device, but its parent claim 19 is directed toward the system. Appropriate correction is required.
Response to Arguments
This office action is in response to amendment filed 11/14/2025. In this action claim(s) 11-27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Claim(s) 11-27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trigonakis et al. (US Pub. No. 20210240705) in view of Belezko et al. (US Pub. No. 20210149851). The Belezko et al. reference has been added to address the amendment of wherein performing non-tree edge verification on the candidate data subgraphs comprises:
based on a respective edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as a valid data subgraph.
Applicant’s arguments:
In regards to claim 1 on Pages 12, applicant argues “It is respectfully submitted that the claimed invention-e.g., independent claim 11, as presented herein, which recites complex parallel processing operations performed via master and worker nodes of a distributed computing system-includes claim limitations that cannot practically be performed in the human mind, and thus the "Mental Process" category does not apply here,” as recited in claim 1.
Examiner’s Reply:
The claims have been evaluated as a whole and when considered in their entirety they still amount to determining ways to search a graph database. The additional data gathering does not add meaningful limitations beyond the abstract idea.
Applicant’s arguments:
In regards to claim 1 on Pages 12, applicant argues “Second, even assuming for the sake of argument that the claimed invention could be characterized as being a mental process, the claimed invention integrates such mental process into a practical application where a particular hardware environment is utilized to merge the processing results of the purported mental processes identified by the Office Action at pages 7- 8,” as recited in claim 1.
Examiner’s Reply:
Graph Modeling is not a technological improvement. The claims merely determines ways to analyze graph using subgraphs. This determination and identification of graph data is a computer-implemented abstract mental process.
Applicant’s arguments:
In regards to claim 1 on Pages 12, applicant argues “Third, the claimed invention, as presented herein, also recites significantly more than the purported mental processes identified by the Office Action at pages 7-8, as the claimed invention includes non-obvious and inventive features not found in conventional systems for processing query graphs (see discussion below regarding distinguishing features of the claimed invention).,” as recited in claim 1.
Examiner’s Reply:
Graph Modeling is well-understood, routine, and conventional. The additional elements merely allow a user to graph data with nodes and edges.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim(s) 11-27 is/are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim 2 and 11 contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. There is no support for “wherein performing non-tree edge verification on the candidate data subgraphs comprises: based on a respective edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as a valid data subgraph; and based on no edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as an invalid data subgraph and discarding the invalid data subgraph.”
Dependent claims 12-15, 17-20, and 22-27 is/are also rejected for inheriting the deficiencies of the independent claims from which they depend on.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 11-27 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
Claim 11-27 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than judicial exception. The eligibility analysis in support of these findings is provided below, on Claim Rejections - 35 USC 101 accordance with the "2019 Revised Patent Subject Matter Eligibility Guidance" (published on 1/7/2019 in Fed, Register, Vol. 84, No. 4 at pgs. 50-57, hereinafter referred to as the "2019 PEG").
Step 1. in accordance with Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is first noted the claim system (claims 11-15), a system (claims 6-20), mediums (claims 21-27) are directed to one of the eligible categories of subject matter and therefore satisfies Step 1.
Step 2A. In accordance with Step 2A, prong one of the 2019 PEG, it is noted that the independent claims recite an abstract idea falling within the Mental Processes enumerated groupings of abstract ideas set forth in the 2019 PEG. Examiner is of the position that independent claims 11, 16, and 21 are directed towards the Mental Process Grouping of Abstract Ideas.
Independent claim(s) 11 recites the following limitations directed towards a Mental Processes:
wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, and-wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node, and wherein each linear sequence has no branching paths;
wherein the master node and the worker nodes are configured to:
search in parallel the data graph for data subgraphs that respectively match the plurality of query subgraphs to obtain candidate data subgraphs to obtain candidate data subgraphs; and (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to search graphs);
perform non-tree edge verification on the candidate data subgraphs (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to perform verification);
wherein performing non-tree edge verification on the candidate data subgraphs comprises:
based on a respective edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as a valid data subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine a candidate subgraph as valid); and
based on no edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as an invalid data subgraph and discarding the invalid data subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine a candidate subgraph as invalid); and
wherein the distributed computing system is configured to merge the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine subgraphs).
Step 2A. In accordance with Step 2A, prong two of the 2019 PEG, the judicial exception is not integrated into a practical application because of the recitation in claim(s) 11:
a distributed computing system, comprising a master node and a plurality of worker nodes (i.e., as a generic processor/component performing a generic computer function);
a distributed storage system in communication with the distributed computing system, wherein the distributed storage system comprises a plurality of storages, wherein each of the plurality of storages corresponds to a respective part of a data graph (i.e., as a generic processor/component performing a generic computer function);
wherein the distributed computing system is configured to receive a search request, indicating a query graph, wherein the query graph is formed by a plurality of nodes and a plurality of edges between the plurality of nodes, wherein each node represents an object, and wherein each edge represents an association relationship between objects (recites insignificant extra solution activity that amounts to mere data gathering).
Step 2B. Similar to the analysis under 2A Prong Two, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Because the additional elements of the independent claims amount to insignificant extra solution activity and/or mere instructions, the additional elements do not add significantly more to the judicial exception such that the independent claims as a whole would be patent eligible.
Independent claim(s) 16 recites the following limitations directed towards a Mental Processes:
partition the query graph into a plurality of query subgraphs using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, and wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to search subgraphs);
search in parallel the data graph for data subgraphs that respectively match the plurality of query subgraphs to obtain candidate data subgraphs (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to search graphs);
perform non-tree edge verification on the candidate data subgraphs (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to perform edge verification);
merge the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine subgraphs);
wherein performing non-tree edge verification on the candidate data subgraphs comprises:
based on a respective edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as a valid data subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine a candidate subgraph as valid); and
based on no edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as an invalid data subgraph and discarding the invalid data subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine a candidate subgraph as invalid).
Step 2A. In accordance with Step 2A, prong two of the 2019 PEG, the judicial exception is not integrated into a practical application because of the recitation in claim(s) 16:
a centralized computing device (i.e., as a generic processor/component performing a generic computer function);
a centralized storage, in communication with the centralized computing device, wherein
the centralized storage is configured to store a data graph (i.e., as a generic processor/component performing a generic computer function);
receive a search request, indicating a query graph, wherein the query graph is formed by a plurality of nodes and a plurality of edges between the plurality of nodes, wherein each node represents an object, and wherein each edge represents an association relationship between objects (recites insignificant extra solution activity that amounts to mere data gathering).
Step 2B. Similar to the analysis under 2A Prong Two, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Because the additional elements of the independent claims amount to insignificant extra solution activity and/or mere instructions, the additional elements do not add significantly more to the judicial exception such that the independent claims as a whole would be patent eligible.
Independent claim(s) 21 recites the following limitations directed towards a Mental Processes:
partitioning, by the computing system, the query graph into a plurality of query subgraphs using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a group of nodes in the plurality of nodes and edges between the group of nodes, wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, and-wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node, and wherein each linear sequence has no branching paths (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to search subgraphs); and
searching, by the computing system, in parallel the data graph for data subgraphs that respectively match the plurality of query subgraphs, to obtain candidate data subgraphs, wherein the data graph is stored by a storage system (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to search graphs);
performing, by the computing system, non-tree edge verification on the candidate data subgraphs (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to perform verification);
merge, by the computing system, the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine subgraphs);
wherein performing non-tree edge verification on the candidate data subgraphs comprises:
based on a respective edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as a valid data subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine a candidate subgraph as valid); and
based on no edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as an invalid data subgraph and discarding the invalid data subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine a candidate subgraph as invalid); and
wherein the distributed computing system is configured to merge the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by using computer as a tool to determine subgraphs).
Step 2A. In accordance with Step 2A, prong two of the 2019 PEG, the judicial exception is not integrated into a practical application because of the recitation in claim(s) 21:
by the computing system (i.e., as a generic processor/component performing a generic computer function);
receiving, by a computer system, a search request, indicating a query graph, wherein the query graph is formed by a plurality of nodes and a plurality of edges between the plurality of nodes, wherein each node represents an object, and wherein each edge represents an association relationship between objects (recites insignificant extra solution activity that amounts to mere data gathering).
Step 2B. Similar to the analysis under 2A Prong Two, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Because the additional elements of the independent claims amount to insignificant extra solution activity and/or mere instructions, the additional elements do not add significantly more to the judicial exception such that the independent claims as a whole would be patent eligible.
Therefore, independent claims 1, 16, and 21 are rejected under 35 U.S.C. 101.
With respect to claim(s) 12, 17, and 22:
Step 2A, prong one of the 2019 PEG:
performing (DFS) on the query graph, by the at least one processor, to transform the query graph into a tree structure, wherein the tree structure comprises the plurality of nodes in the query graph and at least a part of edges in the plurality of edges (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by performing a graph search); and
partitioning the tree structure into the plurality of query subgraphs by the at least one processor, wherein each query subgraph comprises nodes and edges on a path from a root node to a leaf node of the tree structure (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by partitioning a tree structure).
Step 2A Prong Two Analysis:
This judicial exception is not integrated into a practical application because there are no
additional elements to provide practical application.
Step 2B Analysis:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
With respect to claim(s) 13, 18, and 23:
Step 2A, prong one of the 2019 PEG:
wherein the tree structure does not comprise a first edge in the plurality of edges of the query graph, and a first query subgraph in the plurality of query subgraphs comprises a pair of nodes connected through the first edge (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by searching subgraphs); and
wherein searching in parallel the data graph, by the at least one processor, for data subgraphs that respectively match the plurality of query subgraphs (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by searching subgraphs) comprises:
searching the target data graph, by the at least one processor, for a candidate data subgraph that matches the first query subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by searching candidate subgraphs);
determining, by the at least one processor, whether the candidate data subgraph comprises an edge that matches the first edge (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by determining a match); and
responsive to determining that the candidate data subgraph comprises the edge that matches the first edge, determining the candidate data subgraph, by the at least one processor, as a first data subgraph that matches the first query subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by determining a match).
Step 2A Prong Two Analysis:
This judicial exception is not integrated into a practical application because there are no
additional elements to provide practical application.
Step 2B Analysis:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
With respect to claim(s) 14, 19, and 24:
Step 2A, prong one of the 2019 PEG:
wherein at least two search processes are initiated to search in parallel the data graph for the plurality of query subgraphs (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by initiating a search).
Step 2A Prong Two Analysis:
This judicial exception is not integrated into a practical application because there are no
additional elements to provide practical application.
Step 2B Analysis:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
With respect to claim(s) 15, 20, 25:
Step 2A, prong one of the 2019 PEG:
responsive to determining that a second query subgraph and a third query subgraph in the plurality of query subgraphs comprise a same partial path starting from a start node, controlling a first search process in the at least two search processes, by the at least one processor, to search the target data graph for a first partial matching subgraph that matches the same partial path (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by searching for a subgraph);
controlling the first search process, by the at least one processor, to search the target data graph for a second partial matching subgraph that matches a path other than the same partial path in the second query subgraph, wherein the first partial matching subgraph and the second partial matching subgraph are cascaded into a second data subgraph that matches the second query subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by searching for a subgraph); and
controlling a second search process in the at least two search processes, by the at least one processor, to search the target data graph for a third partial matching subgraph that matches a path other than the same partial path in the third query subgraph, wherein the first partial matching subgraph and the third partial matching subgraph are cascaded into a third data subgraph that matches the third query subgraph (The limitation recites a mental process of observation and/or evaluation capable of being performed by the human mind by initiating a search).
Step 2A Prong Two Analysis:
This judicial exception is not integrated into a practical application because there are no
additional elements to provide practical application.
Step 2B Analysis:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
With respect to claim(s) 26:
Step 2A, prong one of the 2019 PEG:
Examiner is of the position the dependent claim is directed toward additional elements.
Step 2A Prong Two Analysis:
wherein the computing system is a distributed computing system comprising a master node and a plurality of worker nodes (i.e., as a generic processor/component performing a generic computer function); and
wherein the storage system is a distributed storage system comprising a plurality of storages (i.e., as a generic processor/component performing a generic computer function).
Step 2B Analysis:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
With respect to claim(s) 27:
Step 2A, prong one of the 2019 PEG:
Examiner is of the position the dependent claim is directed toward additional elements.
Step 2A Prong Two Analysis:
wherein the computing system comprises a centralized computing device (i.e., as a generic processor/component performing a generic computer function); and
wherein the storage system comprises a centralized storage (i.e., as a generic processor/component performing a generic computer function).
Step 2B Analysis:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
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) 11-27 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trigonakis et al. (US Pub. No. 20210240705) in view of Belezko et al. (US Pub. No. 20210149851).
With respect to claim 11, Trigonakis et al. discloses a system, comprising:
a distributed computing system, comprising a master node and a plurality of worker nodes (Paragraph 105 discloses nodes in a multi-node database system may be in the form of a group of computers (e.g. workstations, personal computers) that are interconnected via a network. Alternately, the nodes may be the nodes of a grid, which is composed of nodes in the form of server blades interconnected with other server blades on a rack); and
a distributed storage system in communication with the distributed computing system, wherein the distributed storage system comprises a plurality of storages, wherein each of the plurality of storages corresponds to a respective part of a data graph (Paragraph 111 discloses Database data 102 and 104 may each reside in volatile and/or non-volatile storage, such as first volatile memory 412, second volatile memory 442, first persistent storage 430, and second persistent storage 460 and Paragraph 112 discloses graph database 100 is a distributed database comprising a plurality of databases each stored in a respective one or more storage media);
wherein the distributed computing system is configured to receive a search request, indicating a query graph, wherein the query graph is formed by a plurality of nodes and a plurality of edges between the plurality of nodes, wherein each node represents an object, and wherein each edge represents an association relationship between objects (Paragraph 67 discloses the graph data comprises a plurality of vertices and a plurality of edges that represent relationships between the plurality of vertices, and where the database server instance is implemented by a plurality of processing threads running on a computing device of the DBMS and Paragraph 40 discloses while in BFS mode, processing entities attempt to expand intermediate results that correspond to earlier execution stages of the query);
wherein the distributed computing system is configured to merge the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (Paragraph 38 discloses entities work to produce final query results where possible, thereby restricting the runtime memory required for query execution). Trigonakis et al. does not explicitly disclose wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, and wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node.
However, Belezko et al. teaches wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, and-wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node, and wherein each linear sequence has no branching paths (Paragraph 157 discloses a reduced graph database 416 is obtained. Each equivalence class is represented by a single vertex in the reduced graph database 416 (akin to the quotient graph). The connected-components 418 of the reduced graph database 416 are then determined, e.g., using a breadth-first or depth-first search algorithm, yielding a plurality of connected-components 418A, 418B, 418C);
wherein the master node and the worker nodes are configured to:
search in parallel the data graph for data subgraphs that respectively match the plurality of query subgraphs to obtain candidate data subgraphs to obtain candidate data subgraphs (Paragraph 77 discloses comparing and transforming graph database objects and their query systems and apply the mechanism to the problems in entity resolution, data table relationships, database schema search, and natural language processing and Paragraph 184 discloses Evaluate performance and calculate accuracies. If machine learning algorithms are being used in the loop, e.g., to compute connected-components or in other parts of the algorithm, the system can be evaluated to check if performance objectives are being met. For example, entity matching may be 98.6% correct, while quotient graph, graph transformation may be 100% correct, and the irreducible generators may be 100% correct);
perform non-tree edge verification on the candidate data subgraphs (Paragraph 172 discloses Build graph objects or graph databases based on entity relationships, e.g., common elements. After establishing the common row and column relationship among the tables, the system builds the graph object/database for the relationship: nodes: the tables, Edges: common row and column relations. The first 25 comparisons are displayed by the subgraph of the whole database);
wherein performing non-tree edge verification on the candidate data subgraphs comprises:
based on a respective edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as a valid data subgraph (Paragraph 94 discloses there may be a step of validating the reduced graph database or derivative information thereof to ensure that there is acceptable accuracy or performance gains (in case it introduces errors or isn't actually that helpful), and re-generating a perturbed version of the reduced graph database as required (to be re-validated again). In this example, only after successful validation is the reduced graph database or derivative information used as a stand-in transformed data structure for the data processing operations); and
based on no edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as an invalid data subgraph and discarding the invalid data subgraph (Paragraph 94 discloses there may be a step of validating the reduced graph database or derivative information thereof to ensure that there is acceptable accuracy or performance gains (in case it introduces errors or isn't actually that helpful), and re-generating a perturbed version of the reduced graph database as required (to be re-validated again). In this example, only after successful validation is the reduced graph database or derivative information used as a stand-in transformed data structure for the data processing operations); and
wherein the distributed computing system is configured to merge the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (Paragraph 212 discloses system can merge certain groups of the financial institution's websites together by, for instance, their interconnection scores, to simplify the overall map of all the financial institution's websites and make the financial institution path analysis much smoother and more human perceivable with graph homomorphisms and quotient graphs).
Therefore, it would have been obvious at the time the invention was made to a person having ordinary skill in the art to modify Trigonakis et al. with Belezko et al. to include wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, and-wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node, and wherein each linear sequence has no branching paths. This would have facilitated graph analysis for pattern matching.
The Trigonakis et al. reference as modified by Belezko et al. teaches all the limitations of claim 11. With respect to claim 12, Belezko et al. teaches the system according to claim 11, wherein partitioning the query graph into the plurality of query subgraphs comprises:
performing depth-first search (DFS) on the query graph, to transform the query graph into a tree structure, wherein the tree structure comprises the plurality of nodes in the query graph and at least a part of edges in the plurality of edges (Paragraph 157 discloses a reduced graph database 416 is obtained. Each equivalence class is represented by a single vertex in the reduced graph database 416 (akin to the quotient graph). The connected-components 418 of the reduced graph database 416 are then determined, e.g., using a breadth-first or depth-first search algorithm, yielding a plurality of connected-components 418A, 418B, 418C); and
partitioning the tree structure into the plurality of query subgraphs, wherein each query subgraph comprises nodes and edges on a path from a root node to a leaf node of the tree structure (Paragraph 172 discloses Build graph objects or graph databases based on entity relationships, e.g., common elements. After establishing the common row and column relationship among the tables, the system builds the graph object/database for the relationship: nodes: the tables, Edges: common row and column relations. The first 25 comparisons are displayed by the subgraph of the whole database). The motivation to combine statement previously provided in the rejection of independent claim 1 provided above, combining the Trigonakis et al. reference and the Belezko et al. reference is applicable to dependent claim 2.
The Trigonakis et al. reference as modified by Belezko et al. teaches all the limitations of claim 12. With respect to claim 13, Belezko et al. teaches the system according to claim 13, wherein the tree structure does not comprise a first edge in the plurality of edges of the query graph, and a first query subgraph in the plurality of query subgraphs comprises a pair of nodes connected through the first edge (Paragraphs 109-112 discloses Quotient graphs of G are equivalent to homomorphic images of G. If f:G.fwdarw.H is a graph homomorphism and S is a subgraph of G, then: f(G)=(G)), f(G))) is a subgraph of H. If Q is a query on G then Q can be mapped to a query on H, denoted by f(Q). A complete graph is a graph in which each pair of graph vertices is connected by an edge. A complete graph with n nodes is noted by K.sub.n); and
wherein searching in parallel the data graph for data subgraphs that respectively match the plurality of query subgraphs comprises:
searching the target data graph for a candidate data subgraph that matches the first query subgraph (Paragraphs 109-112 discloses Quotient graphs of G are equivalent to homomorphic images of G. If f:G.fwdarw.H is a graph homomorphism and S is a subgraph of G, then: f(G)=(G)), f(G))) is a subgraph of H. If Q is a query on G then Q can be mapped to a query on H, denoted by f(Q). A complete graph is a graph in which each pair of graph vertices is connected by an edge. A complete graph with n nodes is noted by K.sub.n);
determining whether the candidate data subgraph comprises an edge that matches the first edge (Paragraph 94 discloses there may be a step of validating the reduced graph database or derivative information thereof to ensure that there is acceptable accuracy or performance gains (in case it introduces errors or isn't actually that helpful), and re-generating a perturbed version of the reduced graph database as required (to be re-validated again). In this example, only after successful validation is the reduced graph database or derivative information used as a stand-in transformed data structure for the data processing operations); and
responsive to determining that the candidate data subgraph comprises the edge that matches the first edge, determining the candidate data subgraph as a first data subgraph that matches the first query subgraph (Paragraph 94 discloses there may be a step of validating the reduced graph database or derivative information thereof to ensure that there is acceptable accuracy or performance gains (in case it introduces errors or isn't actually that helpful), and re-generating a perturbed version of the reduced graph database as required (to be re-validated again). In this example, only after successful validation is the reduced graph database or derivative information used as a stand-in transformed data structure for the data processing operations). The motivation to combine statement previously provided in the rejection of dependent claim 12 provided above, combining the Trigonakis et al. reference and the Belezko et al. reference is applicable to dependent claim 13.
The Trigonakis et al. reference as modified by Belezko et al. teaches all the limitations of claim 11. With respect to claim 14, Belezko et al. teaches the system according to claim 11, wherein at least two search processes are initiated to search in parallel the data graph for the plurality of query subgraphs (Paragraph 157 discloses a reduced graph database 416 is obtained. Each equivalence class is represented by a single vertex in the reduced graph database 416 (akin to the quotient graph). The connected-components 418 of the reduced graph database 416 are then determined, e.g., using a breadth-first or depth-first search algorithm, yielding a plurality of connected-components 418A, 418B, 418C. Each connected-component represents a smaller grouping than the full graph database 408 (or reduced graph database 416), and which each can then be manipulated and transformed separately, thereby reducing the computational cost). The motivation to combine statement previously provided in the rejection of dependent claim 11 provided above, combining the Trigonakis et al. reference and the Belezko et al. reference is applicable to dependent claim 14.
The Trigonakis et al. reference as modified by Belezko et al. teaches all the limitations of claim 14. With respect to claim 15, Belezko et al. teaches the electronic device according to claim 14, wherein searching in parallel the data graph for data subgraphs that respectively match the plurality of query subgraphs comprises:
responsive to determining that a second query subgraph and a third query subgraph in the plurality of query subgraphs comprise a same partial path starting from a start node, controlling a first search process in the at least two search processes to search the data graph for a first partial matching subgraph that matches the same partial path (Paragraph 215 discloses between the two graphs (a client from the first graph and the same client from the second graph are matched so that two components are linked so that the system can show better recommendations for products, according to some embodiments);
controlling the first search process to search the data graph for a second partial matching subgraph that matches a path other than the same partial path in the second query subgraph, wherein the first partial matching subgraph and the second partial matching subgraph are cascaded into a second data subgraph that matches the second query subgraph (Paragraph 215 discloses between the two graphs (a client from the first graph and the same client from the second graph are matched so that two components are linked so that the system can show better recommendations for products, according to some embodiments); and
controlling a second search process in the at least two search processes to search the data graph for a third partial matching subgraph that matches a path other than the same partial path in the third query subgraph, wherein the first partial matching subgraph and the third partial matching subgraph are cascaded into a third data subgraph that matches the third query subgraph (Paragraph 215 discloses between the two graphs (a client from the first graph and the same client from the second graph are matched so that two components are linked so that the system can show better recommendations for products, according to some embodiments). The motivation to combine statement previously provided in the rejection of dependent claim 14 provided above, combining the Trigonakis et al. reference and the Belezko et al. reference is applicable to dependent claim 15.
With respect to claim 16, Trigonakis et al. discloses a system, comprising:
a centralized computing device (Paragraph 105 discloses nodes in a multi-node database system may be in the form of a group of computers (e.g. workstations, personal computers) that are interconnected via a network. Alternately, the nodes may be the nodes of a grid, which is composed of nodes in the form of server blades interconnected with other server blades on a rack); and
a centralized storage, in communication with the centralized computing device, wherein the centralized storage is configured to store a data graph (Paragraph 111 discloses Database data 102 and 104 may each reside in volatile and/or non-volatile storage, such as first volatile memory 412, second volatile memory 442, first persistent storage 430, and second persistent storage 460 and Paragraph 112 discloses graph database 100 is a distributed database comprising a plurality of databases each stored in a respective one or more storage media);
wherein the centralized computing device is configured to:
receive a search request indicating a query graph, wherein the query graph is formed by a plurality of nodes and a plurality of edges between the plurality of nodes, wherein each node represents an object, and wherein each edge represents an association relationship between objects (Paragraph 67 discloses the graph data comprises a plurality of vertices and a plurality of edges that represent relationships between the plurality of vertices, and where the database server instance is implemented by a plurality of processing threads running on a computing device of the DBMS and Paragraph 40 discloses while in BFS mode, processing entities attempt to expand intermediate results that correspond to earlier execution stages of the query);
merge the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (Paragraph 38 discloses entities work to produce final query results where possible, thereby restricting the runtime memory required for query execution). Trigonakis et al. does not explicitly disclose wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, and wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node.
However, Belezko et al. teaches wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, and-wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node, and wherein each linear sequence has no branching paths (Paragraph 157 discloses a reduced graph database 416 is obtained. Each equivalence class is represented by a single vertex in the reduced graph database 416 (akin to the quotient graph). The connected-components 418 of the reduced graph database 416 are then determined, e.g., using a breadth-first or depth-first search algorithm, yielding a plurality of connected-components 418A, 418B, 418C);
wherein the master node and the worker nodes are configured to:
search in parallel the data graph for data subgraphs that respectively match the plurality of query subgraphs to obtain candidate data subgraphs to obtain candidate data subgraphs (Paragraph 77 discloses comparing and transforming graph database objects and their query systems and apply the mechanism to the problems in entity resolution, data table relationships, database schema search, and natural language processing and Paragraph 184 discloses Evaluate performance and calculate accuracies. If machine learning algorithms are being used in the loop, e.g., to compute connected-components or in other parts of the algorithm, the system can be evaluated to check if performance objectives are being met. For example, entity matching may be 98.6% correct, while quotient graph, graph transformation may be 100% correct, and the irreducible generators may be 100% correct);
perform non-tree edge verification on the candidate data subgraphs (Paragraph 172 discloses Build graph objects or graph databases based on entity relationships, e.g., common elements. After establishing the common row and column relationship among the tables, the system builds the graph object/database for the relationship: nodes: the tables, Edges: common row and column relations. The first 25 comparisons are displayed by the subgraph of the whole database);
wherein performing non-tree edge verification on the candidate data subgraphs comprises:
based on a respective edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as a valid data subgraph (Paragraph 94 discloses there may be a step of validating the reduced graph database or derivative information thereof to ensure that there is acceptable accuracy or performance gains (in case it introduces errors or isn't actually that helpful), and re-generating a perturbed version of the reduced graph database as required (to be re-validated again). In this example, only after successful validation is the reduced graph database or derivative information used as a stand-in transformed data structure for the data processing operations); and
based on no edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as an invalid data subgraph and discarding the invalid data subgraph (Paragraph 94 discloses there may be a step of validating the reduced graph database or derivative information thereof to ensure that there is acceptable accuracy or performance gains (in case it introduces errors or isn't actually that helpful), and re-generating a perturbed version of the reduced graph database as required (to be re-validated again). In this example, only after successful validation is the reduced graph database or derivative information used as a stand-in transformed data structure for the data processing operations); and
wherein the distributed computing system is configured to merge the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (Paragraph 212 discloses system can merge certain groups of the financial institution's websites together by, for instance, their interconnection scores, to simplify the overall map of all the financial institution's websites and make the financial institution path analysis much smoother and more human perceivable with graph homomorphisms and quotient graphs).
Therefore, it would have been obvious at the time the invention was made to a person having ordinary skill in the art to modify Trigonakis et al. with Belezko et al. to include wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, and-wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node, and wherein each linear sequence has no branching paths. This would have facilitated graph analysis for pattern matching.
With respect to claim 17, it is rejected on grounds corresponding to above rejected claim 12, because claim 17 is substantially equivalent to claim 12.
With respect to claim 18, it is rejected on grounds corresponding to above rejected claim 13, because claim 18 is substantially equivalent to claim 13.
With respect to claim 19, it is rejected on grounds corresponding to above rejected claim 14, because claim 19 is substantially equivalent to claim 14.
With respect to claim 20, it is rejected on grounds corresponding to above rejected claim 15, because claim 20 is substantially equivalent to claim 15.
With respect to claim 21, Trigonakis et al. discloses one or more non-transitory computer-readable mediums having processor- executable instructions stored thereon, wherein the processor-executable instructions, when executed, facilitate performance of the following:
receiving, by a computing system, a search request indicating a query graph, wherein the query graph is formed by a plurality of nodes and a plurality of edges between the plurality of nodes, wherein each node represents an object, and wherein each edge represents an association relationship between objects (Paragraph 67 discloses the graph data comprises a plurality of vertices and a plurality of edges that represent relationships between the plurality of vertices, and where the database server instance is implemented by a plurality of processing threads running on a computing device of the DBMS and Paragraph 40 discloses while in BFS mode, processing entities attempt to expand intermediate results that correspond to earlier execution stages of the query);
merging, by the computing system, the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (Paragraph 38 discloses entities work to produce final query results where possible, thereby restricting the runtime memory required for query execution). Trigonakis et al. does not explicitly disclose wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, and wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node.
However, Belezko et al. teaches wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, and-wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node, and wherein each linear sequence has no branching paths (Paragraph 157 discloses a reduced graph database 416 is obtained. Each equivalence class is represented by a single vertex in the reduced graph database 416 (akin to the quotient graph). The connected-components 418 of the reduced graph database 416 are then determined, e.g., using a breadth-first or depth-first search algorithm, yielding a plurality of connected-components 418A, 418B, 418C);
wherein the master node and the worker nodes are configured to:
search in parallel the data graph for data subgraphs that respectively match the plurality of query subgraphs to obtain candidate data subgraphs to obtain candidate data subgraphs (Paragraph 77 discloses comparing and transforming graph database objects and their query systems and apply the mechanism to the problems in entity resolution, data table relationships, database schema search, and natural language processing and Paragraph 184 discloses Evaluate performance and calculate accuracies. If machine learning algorithms are being used in the loop, e.g., to compute connected-components or in other parts of the algorithm, the system can be evaluated to check if performance objectives are being met. For example, entity matching may be 98.6% correct, while quotient graph, graph transformation may be 100% correct, and the irreducible generators may be 100% correct);
perform non-tree edge verification on the candidate data subgraphs (Paragraph 172 discloses Build graph objects or graph databases based on entity relationships, e.g., common elements. After establishing the common row and column relationship among the tables, the system builds the graph object/database for the relationship: nodes: the tables, Edges: common row and column relations. The first 25 comparisons are displayed by the subgraph of the whole database);
wherein performing non-tree edge verification on the candidate data subgraphs comprises:
based on a respective edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as a valid data subgraph (Paragraph 94 discloses there may be a step of validating the reduced graph database or derivative information thereof to ensure that there is acceptable accuracy or performance gains (in case it introduces errors or isn't actually that helpful), and re-generating a perturbed version of the reduced graph database as required (to be re-validated again). In this example, only after successful validation is the reduced graph database or derivative information used as a stand-in transformed data structure for the data processing operations); and
based on no edge corresponding to a non-tree edge of the query graph existing in a respective candidate data subgraph, determining the respective candidate data subgraph as an invalid data subgraph and discarding the invalid data subgraph (Paragraph 94 discloses there may be a step of validating the reduced graph database or derivative information thereof to ensure that there is acceptable accuracy or performance gains (in case it introduces errors or isn't actually that helpful), and re-generating a perturbed version of the reduced graph database as required (to be re-validated again). In this example, only after successful validation is the reduced graph database or derivative information used as a stand-in transformed data structure for the data processing operations); and
wherein the distributed computing system is configured to merge the data subgraphs that respectively match the plurality of query subgraphs, to determine a search result that matches the query graph (Paragraph 212 discloses system can merge certain groups of the financial institution's websites together by, for instance, their interconnection scores, to simplify the overall map of all the financial institution's websites and make the financial institution path analysis much smoother and more human perceivable with graph homomorphisms and quotient graphs).
Therefore, it would have been obvious at the time the invention was made to a person having ordinary skill in the art to modify Trigonakis et al. with Belezko et al. to include wherein the distributed computing system is configured to partition the query graph into a plurality of query subgraphs, using a depth-first search (DFS)-based hierarchical partitioning algorithm on the query graph, wherein each query subgraph comprises a respective group of nodes in the plurality of nodes and respective edges between the group of nodes, wherein the plurality of query subgraphs have at least one same node in the plurality of nodes, and-wherein each of the plurality of query subgraphs, based on the partitioning, contains a linear sequence of nodes having a same root node, and wherein each linear sequence has no branching paths. This would have facilitated graph analysis for pattern matching.
With respect to claim 22, it is rejected on grounds corresponding to above rejected claim 12, because claim 22 is substantially equivalent to claim 12.
With respect to claim 23, it is rejected on grounds corresponding to above rejected claim 18, because claim 23 is substantially equivalent to claim 18.
With respect to claim 24, it is rejected on grounds corresponding to above rejected claim 19, because claim 24 is substantially equivalent to claim 19.
With respect to claim 25, it is rejected on grounds corresponding to above rejected claim 20, because claim 25 is substantially equivalent to claim 20.
The Trigonakis et al. reference as modified by Belezko et al. teaches all the limitations of claim 21. With respect to claim 26, Trigonakis et al. teaches the one or more non-transitory computer-readable mediums according to claim 21, wherein the computing system is a distributed computing system comprising a master node and a plurality of worker nodes (Paragraph 105 discloses nodes in a multi-node database system may be in the form of a group of computers (e.g. workstations, personal computers) that are interconnected via a network. Alternately, the nodes may be the nodes of a grid, which is composed of nodes in the form of server blades interconnected with other server blades on a rack); and
wherein the storage system is a distributed storage system comprising a plurality of storages (Paragraph 111 discloses Database data 102 and 104 may each reside in volatile and/or non-volatile storage, such as first volatile memory 412, second volatile memory 442, first persistent storage 430, and second persistent storage 460 and Paragraph 112 discloses graph database 100 is a distributed database comprising a plurality of databases each stored in a respective one or more storage media).
The Trigonakis et al. reference as modified by Belezko et al. teaches all the limitations of claim 21. With respect to claim 27, Trigonakis et al. teaches the one or more non-transitory computer-readable mediums according to claim 21, wherein the computing system comprises a centralized computing device (Paragraph 105 discloses nodes in a multi-node database system may be in the form of a group of computers (e.g. workstations, personal computers) that are interconnected via a network. Alternately, the nodes may be the nodes of a grid, which is composed of nodes in the form of server blades interconnected with other server blades on a rack); and
wherein the storage system comprises a centralized storage (Paragraph 111 discloses Database data 102 and 104 may each reside in volatile and/or non-volatile storage, such as first volatile memory 412, second volatile memory 442, first persistent storage 430, and second persistent storage 460 and Paragraph 112 discloses graph database 100 is a distributed database comprising a plurality of databases each stored in a respective one or more storage media).
Relevant Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US PG-PUB 20130080476 is directed to SEARCH APPARATUS, SEARCH METHOD, AND COMPUTER READABLE MEDIUM: [0032] The search statement 1 represents a subgraph having nodes and links, as illustrated in FIG. 1A. In FIG. 1A, the nodes are represented by elliptical shapes, and the links are represented by arrows connecting the elliptical shapes. That is, in the subgraph illustrated in FIG. 1A, the node "Subj-n" has, as an object, the resource specified as <someUri>, and also has the attribute "person" (=foaf:Person type). In the search statement 1 described above, the link (predicate) "pred1" is a variable, and therefore any link matches "pred1" (that is, the relationship between "subj-n" and <someUri> is not limited). In the search statement 1 described above, furthermore, the node "Subj-n" is a variable, and a node "Subj-n" that matches the subgraph described above is a search result.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICHOLAS E ALLEN whose telephone number is (571)270-3562. The examiner can normally be reached Monday through Thursday 830-630.
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/N.E.A/Examiner, Art Unit 2154
/BORIS GORNEY/Supervisory Patent Examiner, Art Unit 2154