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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 23 December 2025 has been entered.
Response to Amendment
This communication is in response to the amendment filed on 23 December 2025.
Claims 1, 14 and 20 are amended.
Claims 1-20 have been examined.
Response to Arguments
In response to Applicant’s remarks filed on 23 December 2025:
a. Applicant's arguments with respect to the 35 U.S.C. 101 rejections of the pending claims have been fully considered but are not deemed persuasive.
On pages 8-12 of Applicant’s remarks, Applicant argues against the 35 U.S.C. 101 rejections of the pending claims. Applicant argues that claim 1 does not recite an abstract idea under Step 2A, Prong One; does recite a practical application under Step 2A, Prong Two; and/or does recite significantly more than an abstract idea under Step 2B.
The Office respectfully disagrees with the above remarks. Applicant points to the newly-added limitations of a) cloud storage across a plurality of storage locations and b) generating a display (remarks, page 9, last two paragraphs). Applicant cites these features to support assertions that the limitations of claim 1 are not practically performable in the human mind and, additionally, that the claim recites a practical application (remarks, page 10, first paragraph). As to the newly-added cloud storage feature, the Office does not dispute that cloud storage in a plurality of locations cannot be performed in the mind. This feature is an additional element (i.e. beyond the abstract idea) that is analyzed at Steps 2A, Prong Two and 2B. The Office disputes the assertion that adding such a high-level, generic recitation of computing functionality and technological environment makes an abstract idea patent eligible. MPEP 2106.05(f) explains:
“As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do "‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’". Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on "the draftsman’s art").”
In addition, MPEP 2106.05(h) explains:
“As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.”
The claimed cloud storage amounts to mere instructions to apply the abstract idea on a computer and/or mere recitation of a particular technological environment in which to practice the invention, neither of which can be deemed a practical application. As to the generating of a display and presenting it on a user interface, this feature also cannot be performed in the mind and hence is not an abstract idea limitation. Rather, it is an additional element analyzed at Steps 2A, Prong Two and 2B. This feature is recited at a high level of generality and amounts to no more than merely outputting a result, which has been deemed which has been deemed by the courts to be insignificant extra-solution activity. See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015); Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016). Hence, it cannot be deemed a practical application. See MPEP 2106.05(g). As detailed below in the claim rejections under 35 U.S.C. 101, claim 1 recites an abstract idea under the “Mental Processes” and/or “Mathematical Concepts” groupings, and the additional elements in the claim are either insignificant extra solution activity (e.g. mere data gathering or outputting), mere instructions to apply the abstract idea on a computer (e.g. (claim 14’s “training a model”), or generic computing components performing generic computing functions (e.g. processor and storage media). None of the additional elements, whether considered individually or as a whole, can be deemed a practical application or an inventive concept, for the reasons detailed below in the claim rejections under 35 U.S.C. 101. Claim 1 is not patent eligible.
Claims 14 and 20 recite limitations similar to those of claim 1 and are ineligible under 35 U.S.C. 101 for the same reasons that claim 1 is ineligible, as set forth above.
Claims 2-13 and 15-19 are ineligible under 35 U.S.C. 101 for the same reasons that claims 1, 14, and 20 are ineligible, as set forth above, and for the additional reasons detailed below in the claim rejections under 35 U.S.C. 101.
b. Applicant's arguments with respect to the 35 U.S.C. 103 rejections of the pending claims have been fully considered but are not deemed persuasive.
On pages 12-14 of Applicant’s remarks, Applicant argues that the cited prior art fails to teach or suggest the limitations of claim 1. In support of this argument, Applicant asserts that Harris and Yuan fail to teach or suggest “generation of graph data models that connected structured data (e.g., "first element") and unstructured data (e.g., "one or more second elements") through transformation of such data, where such graph data models are used for responding to queries that identify "first element" as one of its parameters, where the data is stored in a plurality of storage locations and where in the graph data model the plurality of nodes are connected using the plurality of connections” (remarks, page 14, first full paragraph).
The Office respectfully disagrees with the above remarks. Firstly, the specification of structured versus unstructured is merely a recitation of the type of data upon which to implement the technique of the invention and in no way limits the claimed technique. Hence, these limitations amount to no more than an intended use of the claimed invention and have no patentable weight. However, assuming arguendo that these limitations (i.e. “structured data elements” and “unstructured data elements”) have patentable weight, prior art is cited. Secondly, the claimed “structured data element” is interpreted in light of the instant specification, which states the following: “The structured data may be any organized data that conforms to a certain format.” See para. 0023 of Applicant’s published specification. The claimed “unstructured data elements” are interpreted in light of the instant specification, which describes unstructured data as textual data. See para. 0025 of Applicant’s specification. Harris teaches receiving graph query 850 for querying a graph database (Harris para. 0159-0160 and Fig. 8), the query identifying at least one first element in the plurality of elements stored in the graph database for retrieval (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph). Harris further teaches that graph nodes represent transaction data and/or user profile data (Harris para. 0062), and hence at least these graph nodes represent structured data elements. Harris also teaches that nodes of the graph correspond to textual data (Harris para. 0062), and hence at least these graph nodes represent unstructured data elements. Regarding the claimed “transforming the data into a plurality of nodes and one or more a plurality of connections connecting at least two nodes in the plurality of nodes, wherein at least one node in the plurality of nodes includes the at least one first element,” Harris teaches a graph having nodes connected by edges (see Harris para. 0031 and Fig. 2), and as set forth above, at least some of those nodes correspond to structured data elements. Harris teaches responding to the received query by outputting results to a display (Harris para. 0005, 0162, 0199, and Fig. 8). Furthermore, Harris teaches that graph sharding is used to split up the graph for processing in a distributed processing framework (Harris para. 0174, 0176, and Fig. 10) Hence, Harris teaches all of the above-cited features of claim 1. Furthermore, Yuan teaches these features as well, as detailed below in the claim rejections under 35 U.S.C. 103.
Applicant also asserts that Harris and Yuan fail to teach or suggest the claimed “generating a display of the at least one first element and the selected at least one second element in a hierarchical structure and presenting the display on a user interface.” However, Yuan teaches that results are displayed in tree form Yuan (Yuan para. 0049), which is a type of hierarchical structure. Both Harris and Yuan teach outputting results for display in a user interface (Harris para. 0199 and Yuan Fig. 7). Therefore, the cited prior art teaches the features of claim 1 as claimed.
Claims 14 and 20 recite limitations similar to those of claim 1 and are unpatentable over the prior art for the same reasons that claim 1 is unpatentable, as set forth above.
Claims 2-13 and 15-19 are unpatentable over the prior art for the same reasons that claims 1, 14, and 20 are unpatentable, as set forth above.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
As to claims 1, 14, and 20, these claims recite “data stored in a graph database, the data being stored using one or more graph data models having a plurality of elements connected using a plurality of connections.” The broadest reasonable interpretation (BRI) of this limitation requires just two elements connected by just two connections. The claims also recite identifying a graph data model associated with a received query. The claimed identifying amounts to no more than an evaluation or judgement, which can be mentally performed by a human with the aid of pencil and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with a pencil and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. In these claims, the “graph data model” is generated “by transforming the data into a plurality of nodes and one or more connections connecting at least two nodes in the plurality of nodes, wherein at least one node in the plurality of nodes includes the at least one first element.” The claim does not specify nor place any limits upon the number nodes and connections in the graph data model, other than specifying “at least two nodes” and “one or more connections.” Hence, the BRI of the claimed “graph data model” encompasses a simple graph having just two nodes and just one connection. A human could mentally “generate” such a simple graph data model by visualizing it in the mind and/or drawing it out on a piece of paper. Hence, generating the claimed “graph data model” is an abstract idea under the “Mental Processes” grouping.
The claims also recite executing a text-similarity detection to identify one or more second elements in the plurality of elements related to the at least one first element and one or more connections in the plurality of connections associated with at least one of the one or more second elements and the at least one first element. Given that the BRI of the claims encompasses a simple case, as set forth above, a human could mentally perform the claimed text-similarity detection with the aid of pencil and paper. For example, a human could mentally determine that the first element is similar to the second element. Hence, this limitation also falls within the “Mental Processes” grouping of abstract ideas.
These claims also recite “the one or more connections are identified using a similarity score determined based on the text-similarity detection and being above a similarity threshold.” Given that the BRI of claims encompass a simple case, as set forth above, a human could mentally determine a similarity score and judge whether or not that score is above a similarity threshold, as recited in these claims. Hence, this limitation is also an abstract idea under the “Mental Processes” grouping. Alternatively, this limitation may be deemed an abstract idea under the “Mathematical Concepts” grouping, because computing the similarity score and judging whether or not it’s above a similarity threshold are mathematical calculations/operations.
These claims also recite “selecting at least one second element in the one or more second elements and at least one connection in the identified one or more connections responsive to the query.” Given that the BRI of the claims encompasses a simple case, as set forth above, a human could mentally perform the claimed selecting with the aid of pencil and paper. For example, a human could look at a graph drawn out on a piece of paper to answer the query “Which nodes are connected to element A in the graph?” For the simple graph encompassed by the BRI of the claims, it would be easy to select at least one element and connection in the graph that satisfy the query. Hence, this limitation is also an abstract idea under the “Mental Processes” grouping.
These claims also recite the following: “the at least one first element is stored as a structured data element” and “the one or more second elements are stored as unstructured data elements.” These limitations are interpreted in light of the instant specification, which describes structured data as data that conforms to a certain format (see para. 0022 of Applicant’s published specification) and describes unstructured data such as text that is not organized in a predefined manner (see para. 0024 of Applicant’s published specification). Given that the BRI of the claims encompasses a simple case, as set forth above, specifying that certain data elements are structured and others are unstructured does not change the fact that a human can mentally perform the claim limitations described above. Hence, the claim limitations described above are abstract ideas under the “Mental Processes” and/or “Mathematical Concepts” groupings, as set forth above. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. Other than the abstract idea, the claims recite the following:
a) “receiving, by at least one processor, a query for retrieving data stored in a graph database, the data being stored using one or more graph data models having a plurality of elements connected using a plurality of connections, the query identifying at least one first element in the plurality of elements
stored in the graph database for retrieval, the at least one first element is stored as a structured data element, the graph database is a cloud-based graph database storing data in a plurality of storage locations” (claim 1 and similar limitations of claims 14 and 20);
b) training at least one model to identify one or more connections in the plurality of connections associated with at least one of: one or more second elements in the plurality of elements related to the at least one first element, the one or more second elements are stored as unstructured data elements, and the at least one first element, the one or more connections are identified using a similarity score determined based on a text-similarity detection and being above a similarity threshold (claim 14);
c) outputting the at least one first element and the selected at least one second element, and generating a display of the at least one first element and the selected at least one second element in a hierarchical structure and presenting the display on a user interface;
d) at least one processor;
e) at least one non-transitory storage media storing instructions.
Limitation (a) amounts to no more than mere data gathering, which has been deemed by the courts to be insignificant extra-solution activity. See MPEP 2106.05(g). Limitation (b) is recited at a high level of generality and amounts to mere instructions to apply the abstract idea on a computer, which cannot provide a practical application. See MPEP 2106.05(f). Limitation (c) amounts to no more than merely outputting a result, which has been deemed which has been deemed by the courts to be insignificant extra-solution activity. See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015); Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016). See MPEP 2106.05(g). Limitations (d) and (e) are recited at a high level of generality, i.e. as generic computer components performing generic computing functions. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Looking at the additional elements as a whole adds nothing beyond the additional elements considered individually—they still represent insignificant extra-solution activity and/or generic computer implementation. Hence, the claims as a whole, looking at the additional elements individually and in combination, do not integrate the abstract idea into a practical application. The claims are directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Limitation (a) amounts to no more than mere data gathering, which has been deemed by the courts to be insignificant extra-solution activity. See MPEP 2106.05(g). In addition, the courts have deemed receiving data to be well-understood, routine, and conventional activity, as in the following cases: Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015) (storing and retrieving information in memory). See MPEP 2106.05(d)(II). Limitation (b) is recited at a high level of generality and amounts to mere instructions to apply the abstract idea on a computer, which cannot provide a practical application. See MPEP 2106.05(f). Limitation (c) amounts to no more than merely outputting a result, which has been deemed which has been deemed by the courts to be insignificant extra-solution activity. See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015); Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016). See MPEP 2106.05(g). Furthermore, merely outputting elements of a graph in the manner recited in the claims is well-understood, routine, and conventional activity1. Hence, none of elements (a) through (c) provide an inventive concept. As discussed above with respect to integration of the abstract idea into a practical application, additional elements (d) and (e) amount to no more than mere field of use limitations and instructions to apply the exception using generic computer components. Mere instructions to apply an exception using conventional computer components and functions cannot provide an inventive concept. Looking at the additional elements as a whole adds nothing beyond the additional elements considered individually—they still represent insignificant extra-solution activity; well-understood, routine, and conventional subject matter; and/or generic computer implementation. Hence, the claim as a whole, looking at the additional elements individually and in combination, does not amount to significantly more than the abstract idea. These claims are not patent eligible.
As to dependent claims 2-3 and 15, these claims merely recite more details of the claimed training of a model. However, these claims remain at a high level of generality and amount to mere instructions to apply the abstract idea on a computer, which cannot provide a practical application nor an inventive concept. See MPEP 2106.05(f).
As to dependent claims 4 and 16, these claims merely recite details of the type of data stored. This amounts to no more than description of a field of use and/or technological environment, which cannot provide a practical application nor an inventive concept. See MPEP 2106.05(h).
As to dependent claims 5-7 and 17, these claims merely recite more details of the claimed similarity detection. However, given that the BRI of the claims encompasses a simple graph, as set forth above, nothing in these claims goes beyond what a human could mentally perform with the aid of pencil and paper. Hence, these claims remain directed to an abstract idea under the “Mental Processes” and/or “Mathematical Concepts” groupings, without reciting significantly more.
As to dependent claims 8 and 10, these claims merely recite more details of the claimed selecting. However, given that the BRI of the claims encompasses a simple graph, as set forth above, nothing in these claims goes beyond what a human could mentally perform with the aid of pencil and paper. Hence, these claims remain directed to an abstract idea under the “Mental Processes” grouping, without reciting significantly more.
As to dependent claims 9 and 11, these claims merely recite more details of the received query. However, the “receiving a query” limitations of the independent claims remains insignificant extra-solution in the form of data gathering, which cannot provide a practical application, as set forth above in the discussion of the parent claims. Furthermore, receiving a query as described in these claims still remains well-understood, routine, and conventional activity based on the court cases set forth above in the parent claims. Looking at the additional elements as a whole adds nothing beyond the additional elements considered individually—they still represent insignificant extra-solution activity; well-understood, routine, and conventional subject matter; and/or generic computer implementation. Hence, the claims as a whole, looking at the additional elements individually and in combination, do not amount to a practical application nor an inventive concept.
As to dependent claims 12 and 13, these claims merely recite more details of the identified connections. However, given that the BRI of the claims encompasses a simple graph, as set forth above, nothing in these claims goes beyond what a human could mentally perform with the aid of pencil and paper. Hence, these claims remain directed to an abstract idea under the “Mental Processes” grouping, without reciting significantly more.
As to dependent claim 18, see the discussions of claims 8 and 9 above.
As to dependent claim 19, see the discussions of claims 10 and 11 above.
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 of this title, 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.
Claims 1-7, 12-17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Harris et al. (U.S. Patent Application Publication No. 20180330258 A1, hereinafter referred to as Harris) in view of Yuan et al. (U.S. Patent Application Publication No. 20220075948 A1, hereinafter referred to as Yuan).
As to claim 1, Harris teaches a computer-implemented method, comprising:
receiving, by at least one processor (see Harris para. 0197: method of the invention is performed by a processor), a query for retrieving data stored in a graph database (see Harris para. 0159-0160 and Fig. 8: graph query 850 for querying a graph database), the data being stored using one or more graph data models having a plurality of elements connected using a plurality of connections (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges; Note: Harris’ nodes correspond to the claimed “elements” and Harris’ edges correspond to the claimed “connections”), the query identifying at least one first element in the plurality of elements stored in the graph database for retrieval (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph), the at least one first element is stored as a structured data element (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that this limitation has patentable weight, prior art is cited. Note also: The claimed “structured data element” is interpreted in light of the instant specification, which states the following: “The structured data may be any organized data that conforms to a certain format.” See para. 0023 of Applicant’s published specification.
see Harris para. 0062: graph nodes represent transaction data and/or user profile data), the graph database is a graph database storing data in a plurality of storage locations (Harris para. 0174, 0176, and Fig. 10: graph is sharded for processing by a distributed processing framework);
identifying, by the at least one processor, a graph data model in the one or more graph data models (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges) associated with the query, the graph data model being generated using the at least one first element (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph) by transforming the data into a plurality of nodes and one or more connections connecting at least two nodes in the plurality of nodes (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges), wherein at least one node in the plurality of nodes includes the at least one first element (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph);
executing, by the at least one processor, a similarity detection (see Harris para. 0050: determining similarity between nodes) to identify, using the graph data model, one or more second elements in the plurality of elements related to the at least one first element and one or more connections in the plurality of connections associated with at least one of the one or more second elements and the at least one first element (see Harris para. 0160-0162 and Fig. 8: using the graph to determine a list of recommendations and corresponding inferred edges), the one or more second elements are stored as unstructured data elements (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “unstructured data elements” are interpreted in light of the instant specification, which describes unstructured data as textual data. See para. 0025 of Applicant’s specification.
see Harris para. 0062: nodes of the graph correspond to textual data);
selecting, by the at least one processor, at least one second element in the one or more second elements and at least one connection in the identified one or more connections responsive to the query (see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges); and
outputting, by the at least one processor, the at least one first element and the selected at least one second element (see Harris para. 0005: the system outputs results; and see Harris para. 0162 and Fig. 8: returning a list of recommendations for the requesting user); and
generating a display of the at least one first element and the selected at least one second element and presenting the display on a user interface (Harris para. 0199 results displayed on a computer monitor).
Harris does not appear to explicitly disclose the graph database is a cloud-based graph database; a text-similarity detection; and one or more connections are identified using a similarity score determined based on the text-similarity detection and being above a similarity threshold; and a display of a hierarchical structure.
However, Yuan teaches:
the graph database is a cloud-based graph database storing data in a plurality of storage locations (see Yuan 0033 and Fig. 7: cloud-based, distributed computing system; and see Yuan para. 0036: distributed graph database);
receiving, by at least one processor, a query for retrieving data stored in a graph database (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 505, query is a received), the data being stored using one or more graph data models having a plurality of elements connected using a plurality of connections (see Yuan para. 0022 and Figs. 4A-B: graph having vertices/nodes/entities connected by edges; Note: Yuan’s vertices/nodes/entities correspond to the claimed elements and Yuan’s edges correspond to the claimed connections), the query identifying at least one first element in the plurality of elements stored in the graph database for retrieval (see Yuan para. 0025: the query specifies one or more entities associated with the graph), the at least one first element is stored as a structured data element (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “structured data element” is interpreted in light of the instant specification, which states the following: “The structured data may be any organized data that conforms to a certain format.” See para. 0023 of Applicant’s published specification.
see Yuan para. 0022: the graph comprised of vertices and edges conforms to a particular data structure; and see Yuan para. 0025: Structured Query Language (SQL));
executing, by the at least one processor, a text-similarity detection (see Yuan para. 0062-0063: textual similarity) to identify, using the graph data model (see Yuan para. 0022 and Figs. 4A-B: graph having vertices/nodes/entities connected by edges), one or more second elements in the plurality of elements related to the at least one first element and one or more connections in the plurality of connections associated with at least one of the one or more second elements and the at least one first element (see Yuan para. 0053: detecting similar entities and/or relationships in a graph; and see Yuan para. 0062-0063: the similarity is textual similarity), the one or more second elements are stored as unstructured data elements (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “unstructured data elements” are interpreted in light of the instant specification, which describes unstructured data as textual data. See para. 0025 of Applicant’s specification.
see Yuan para. 0021: unstructured text), the one or more connections are identified using a similarity score determined based on the text-similarity detection and being above a similarity threshold (see Yuan para. 0053 and 0062-0063: similarity score above a threshold);
selecting, by the at least one processor, at least one second element in the one or more second elements and at least one connection in the identified one or more connections responsive to the query (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 510, the query is answered based on the graph); and
outputting, by the at least one processor, the at least one first element and the selected at least one second element (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 515, query answer is output); and
generating a display of the at least one first element and the selected at least one second element in a hierarchical structure and presenting the display on a user interface (see Yuan para. 0049: results output in tree form; and see Yuan Fig. 7: outputting to display of computing device(s) 54).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Harris to include the teachings of Yuan because it allows more accurate query answering based on cross document reasoning developed from the graph (see Yuan para. 0053).
As to claim 2, Harris as modified by Yuan teaches wherein the executing includes training at least one model (see Harris para. 0005 and Fig. 1: training a model using historical data about connections between nodes; and see Yuan para. 0024: training a model) to identify the one or more connections in the plurality of connections (see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges; and see Yuan para. 0053: detecting similar entities and/or relationships in a graph).
As to claim 3, Harris as modified by Yuan teaches wherein the at least one model is trained using data associated with one or more historical connections between one or more elements in the plurality of elements (see Harris para. 0005 and Fig. 1: training a model using historical data about connections between nodes).
As to claim 4, this claim merely recites the type of data acted upon by the claimed method, without reciting any limitations that limit the claimed method. Hence, this claim amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited.
Harris as modified by Yuan teaches wherein the graph database is configured to store at least one of the following: a structured data (see Harris para. 0025: data in the graph database is organized to conform to a particular format; and see Yuan para. 0022: the graph comprised of vertices and edges conforms to a particular data structure; and see Yuan para. 0025: Structured Query Language (SQL)), an unstructured data (see Yuan para. 0021: unstructured text), and any combination thereof.
As to claim 5, Harris as modified by Yuan teaches wherein the similarity detection identifying the one or more second elements includes at least one of the following similarities: an element name similarity, an element type similarity, an element text similarity, and any combination thereof (see Harris para. 0050: determining similarity between nodes; and see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges; and see Yuan para. 0062-0063: textual similarity and similarity of named entities).
As to claim 6, Harris as modified by Yuan teaches wherein the similarities are detected between at least one of the following: the at least one first element and the one or more second elements, the one or more second elements, at least another element in the plurality of elements and at least one of the at least one first element and the one or more second elements, and any combination thereof (see Harris para. 0050: determining similarity between nodes; and see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges; and see Yuan para. 0053: detecting similar entities and/or relationships in a graph; and see Yuan para. 0062-0063: the similarity is textual similarity).
As to claim 7, Harris as modified by Yuan teaches wherein the similarity detection is executed using at least one of the following: a structured machine learning (see Harris para. 0109: structured machine learning) by training one or more models with a data set of elements (see Harris para. 0005 and Fig. 1: training a model using historical data about connections between nodes), an unstructured learning (see Yuan para. 0067: machine learning model for natural language processing; and see Yuan para. 0021: unstructured text), and any combinations thereof.
As to claim 12, Harris as modified by Yuan teaches wherein the one or more connections are identified based on at least one of the following: the identified one or more second elements, the at least one first element, and any combination thereof (see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges).
As to claim 13, Harris as modified by Yuan teaches wherein the one or more connections include at least one of the following: a direct connection, an indirect connection, and any combination thereof (see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges).
As to claim 14, Harris teaches a system, comprising:
at least one processor (see Harris para. 0197: method of the invention is performed by a processor); and
at least one non-transitory storage media storing instructions, that when executed by the at least one processor, cause the at least one processor to perform operations including (see Harris para. 0198: computer readable medium storing instructions to be executed by the processor)
receiving a query for retrieving data stored in a graph database (see Harris para. 0159-0160 and Fig. 8: graph query 850 for querying a graph database), the data being stored using one or more graph data models having a plurality of elements connected using a plurality of connections (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges; Note: Harris’ nodes correspond to the claimed “elements” and Harris’ edges correspond to the claimed “connections”), the query identifying at least one first element in the plurality of elements stored in the graph database for retrieval (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph), the at least one first element is stored as a structured data element (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “structured data element” is interpreted in light of the instant specification, which states the following: “The structured data may be any organized data that conforms to a certain format.” See para. 0023 of Applicant’s published specification.
see Harris para. 0062: graph nodes represent transaction data and/or user profile data);
identifying a graph data model in the one or more graph data models (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges) associated with the query, the graph data model being generated using the at least one first element (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph) by transforming the data into a plurality of nodes and one or more connections connecting at least two nodes in the plurality of nodes (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges), wherein at least one node in the plurality of nodes includes the at least one first element (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph);
training at least one model to identify one or more connections in the plurality of connections (see Harris para. 0005 and Fig. 1: training a model using historical data about connections between nodes) associated with at least one of: one or more second elements in the plurality of elements related to the at least one first element, and the at least one first element (see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges), the one or more second elements are stored as unstructured data elements (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “unstructured data elements” are interpreted in light of the instant specification, which describes unstructured data as textual data. See para. 0025 of Applicant’s specification.
see Harris para. 0062: nodes of the graph correspond to textual data);
selecting at least one second element in the one or more second elements and at least one connection in the identified one or more connections responsive to the query (see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges); and
outputting the at least one first element and the selected at least one second element (see Harris para. 0005: the system outputs results; and see Harris para. 0162 and Fig. 8: returning a list of recommendations for the requesting user).
Harris does not appear to explicitly disclose one or more connections are identified using a similarity score determined based on a text-similarity detection and being above a similarity threshold.
However, Yuan teaches:
receiving, by at least one processor, a query for retrieving data stored in a graph database (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 505, query is a received), the data being stored using one or more graph data models having a plurality of elements connected using a plurality of connections (see Yuan para. 0022 and Figs. 4A-B: graph having vertices/nodes/entities connected by edges; Note: Yuan’s vertices/nodes/entities correspond to the claimed elements and Yuan’s edges correspond to the claimed connections), the query identifying at least one first element in the plurality of elements stored in the graph database for retrieval (see Yuan para. 0025: the query specifies one or more entities associated with the graph), the at least one first element is stored as a structured data element (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “structured data element” is interpreted in light of the instant specification, which states the following: “The structured data may be any organized data that conforms to a certain format.” See para. 0023 of Applicant’s published specification.
see Yuan para. 0022: the graph comprised of vertices and edges conforms to a particular data structure; and see Yuan para. 0025: Structured Query Language (SQL));
training at least one model (see Yuan para. 0024: training a model) to identify one or more connections in the plurality of connections associated with at least one of: one or more second elements in the plurality of elements related to the at least one first element, and the at least one first element (see Yuan para. 0053: detecting similar entities and/or relationships in a graph), the one or more second elements are stored as unstructured data elements (Note: The claimed “unstructured data elements” are interpreted in light of the instant specification, which describes unstructured data as textual data. See para. 0025 of Applicant’s specification.
see Yuan para. 0021: unstructured text), the one or more connections are identified using a similarity score determined based on a text-similarity detection and being above a similarity threshold (see Yuan para. 0062-0063: textual similarity; and see Yuan para. 0053 and 0062-0063: similarity score above a threshold);
selecting at least one second element in the one or more second elements and at least one connection in the identified one or more connections responsive to the query (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 510, the query is answered based on the graph); and
outputting the at least one first element and the selected at least one second element (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 515, query answer is output).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Harris to include the teachings of Yuan because it allows more accurate query answering based on cross document reasoning developed from the graph (see Yuan para. 0053).
As to claim 15, see the rejection claim 3 above.
As to claim 16, see the rejection claim 4 above.
As to claim 17, see the rejection claim 6 above.
As to claim 20, Harris teaches a computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations (see Harris para. 0198: computer readable medium storing instructions to be executed by a processor) comprising:
receiving a query for retrieving data stored in a graph database (see Harris para. 0159-0160 and Fig. 8: graph query 850 for querying a graph database), the data being stored using one or more graph data models having a plurality of elements connected using a plurality of connections (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges; Note: Harris’ nodes correspond to the claimed “elements” and Harris’ edges correspond to the claimed “connections”), the query identifying at least one first element in the plurality of elements stored in the graph database for retrieval (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph), the at least one first element is stored as a structured data element (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “structured data element” is interpreted in light of the instant specification, which states the following: “The structured data may be any organized data that conforms to a certain format.” See para. 0023 of Applicant’s published specification.
see Harris para. 0062: graph nodes represent transaction data and/or user profile data);
identifying at least one graph data model in the one or more graph data models (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges) associated with the query, the graph data model being generated using the at least one first element (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph) by transforming the data into a plurality of nodes and one or more connections connecting at least two nodes in the plurality of nodes (see Harris para. 0031 and Fig. 2: graph having nodes connected by edges), wherein at least one node in the plurality of nodes includes the at least one first element (see Harris para. 0162 and Fig. 8: the graph query/request is from a user who is represented by a node in the graph);
executing a similarity detection (see Harris para. 0050: determining similarity between nodes) to identify, using the at least one graph data model, one or more second elements in the plurality of elements related to the at least one first element and one or more connections in the plurality of connections associated with at least one of the one or more second elements and the at least one first element (see Harris para. 0160-0162 and Fig. 8: using the graph to determine a list of recommendations and corresponding inferred edges), the one or more second elements are stored as unstructured data elements (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “unstructured data elements” are interpreted in light of the instant specification, which describes unstructured data as textual data. See para. 0025 of Applicant’s specification.
see Harris para. 0062: nodes of the graph correspond to textual data), wherein the similarities are detected between at least one of the following: the at least one first element and the one or more second elements, the one or more second elements, at least another element in the plurality of elements and at least one of the at least one first element and the one or more second elements, and any combination thereof (see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges),
selecting at least one second element in the one or more second elements and at least one connection in the identified one or more connections responsive to the query (see Harris para. 0162 and Fig. 8: determining a list of recommendations and corresponding inferred edges); and
outputting the at least one first element and the selected at least one second element (see Harris para. 0005: the system outputs results; and see Harris para. 0162 and Fig. 8: returning a list of recommendations for the requesting user).
Harris does not appear to explicitly disclose a text-similarity detection; and one or more connections are identified using a similarity score determined based on the text-similarity detection and being above a similarity threshold.
However, Yuan teaches:
receiving, by at least one processor, a query for retrieving data stored in a graph database (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 505, query is a received), the data being stored using one or more graph data models having a plurality of elements connected using a plurality of connections (see Yuan para. 0022 and Figs. 4A-B: graph having vertices/nodes/entities connected by edges; Note: Yuan’s vertices/nodes/entities correspond to the claimed elements and Yuan’s edges correspond to the claimed connections), the query identifying at least one first element in the plurality of elements stored in the graph database for retrieval (see Yuan para. 0025: the query specifies one or more entities associated with the graph), the at least one first element is stored as a structured data element (Note: This limitation merely recites the type of data acted upon, without reciting any features that limit the claimed technique. Hence, this limitation amounts to no more than an intended use of the claimed invention and it has no patentable weight. However, assuming arguendo that the claim has patentable weight, prior art is cited. Note also: The claimed “structured data element” is interpreted in light of the instant specification, which states the following: “The structured data may be any organized data that conforms to a certain format.” See para. 0023 of Applicant’s published specification.
see Yuan para. 0022: the graph comprised of vertices and edges conforms to a particular data structure; and see Yuan para. 0025: Structured Query Language (SQL));
executing a text-similarity detection (see Yuan para. 0062-0063: textual similarity) to identify, using the at least one graph data model (see Yuan para. 0022 and Figs. 4A-B: graph having vertices/nodes/entities connected by edges), one or more second elements in the plurality of elements related to the at least one first element and one or more connections in the plurality of connections associated with at least one of the one or more second elements and the at least one first element (see Yuan para. 0053: detecting similar entities and/or relationships in a graph; and see Yuan para. 0062-0063: the similarity is textual similarity), the one or more second elements are stored as unstructured data elements (Note: The claimed “unstructured data elements” are interpreted in light of the instant specification, which describes unstructured data as textual data. See para. 0025 of Applicant’s specification.
see Yuan para. 0021: unstructured text), wherein the similarities are detected between at least one of the following: the at least one first element and the one or more second elements, the one or more second elements, at least another element in the plurality of elements and at least one of the at least one first element and the one or more second elements, and any combination thereof (see Yuan para. 0053: detecting similar entities and/or relationships in a graph; and see Yuan para. 0062-0063: the similarity is textual similarity), the one or more connections are identified using a similarity score determined based on the text-similarity detection and being above a similarity threshold (see Yuan para. 0053 and 0062-0063: similarity score above a threshold);
selecting at least one second element in the one or more second elements and at least one connection in the identified one or more connections responsive to the query (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 510, the query is answered based on the graph); and
outputting the at least one first element and the selected at least one second element (see Yuan para. 0025, 0036, and Fig. 1: query 110 for retrieving data from a graph; and see Yuan Fig. 5A: at step 515, query answer is output).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Harris to include the teachings of Yuan because it allows more accurate query answering based on cross document reasoning developed from the graph (see Yuan para. 0053).
Claims 8-11 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Harris and Yuan as applied to claims 1 and 14 above, and further in view of Xie et al. (U.S. Patent Application Publication No. 20100309206 A1, hereinafter referred to as Xie).
As to claim 8, Harris as modified by Yuan does not appear to explicitly disclose wherein the selecting includes selecting the at least one second element in the one or more second elements based on a predetermined number of connections associated with at least one of: the at least one second element, the at least one first element, and any combinations thereof.
However, Xie teaches wherein the selecting includes selecting the at least one second element in the one or more second elements based on a predetermined number of connections associated with at least one of: the at least one second element, the at least one first element, and any combinations thereof (see Xie para. 0030, 0033, and claim 7: nodes are selected as similar based on a user-specified number of links between nodes).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Harris as modified by Yuan to include the teachings of Xie because it gives the user greater control over the clustering/similarity analysis (see Xie para. 0029).
As to claim 9, Harris as modified by Yuan and Xie teaches wherein the received query identifies the predetermined number of connections (see Xie para. 0030, 0033, and claim 7: nodes are selected as similar based on a user-specified number of links between nodes).
As to claim 10, Harris as modified by Yuan does not appear to explicitly disclose wherein the selecting includes selecting a predetermined number of second elements in the one or more second elements.
However, Xie teaches wherein the selecting includes selecting a predetermined number of second elements in the one or more second elements (see Xie para. 0031, 0034, and claim 7: nodes are selected as similar based on a user-specified minimum number of nodes).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Harris as modified by Yuan to include the teachings of Xie because it gives the user greater control over the clustering/similarity analysis (see Xie para. 0029).
As to claim 11, Harris as modified by Yuan and Xie teaches wherein the received query identifies the predetermined number of second elements (see Xie para. 0031, 0034, and claim 7: nodes are selected as similar based on a user-specified minimum number of nodes).
As to claim 18, see the rejection claims 8 and 9 above.
As to claim 19, see the rejection claims 10 and 11 above.
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/Umar Mian/
Examiner, Art Unit 2163
1 See the following:
Leida et al., U.S. PGPub. No. 20130262443 A1, para. 0013; (continued…)
Grinstein et al. U.S. PGPub. No. 20060218563 A1, para. 0024;
Lee et al. U.S. PGPub. No. 20090198725 A1, para. 0003; and/or
Tran, Bao U.S. PGPub. No. 20050182755 A1, para. 0078.