DETAILED ACITON
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 7th 2025 has been entered.
Response to Amendment
3. The Amendment filed on November 7th 2025 has been entered. Claims 1 and 15 have been amended, claims 1 - 20 are pending in the application.
Response to Arguments
35 U.S.C. §102/103
4. Applicant's arguments, see Remarks pp. 7 -9, November 7th 2025, with
respect to the rejections of claims 1-20 under 35 U.S.C. §103 have been fully
considered but they are persuasive in part and non-persuasive in part.
Applicant argues that the prior art cited is in a different area of endeavor than that of claimed invention and further the amendments made to the independent claims overcome the anticipatory review of the Saxena reference.
In response to applicant's argument that the Saxena reference is nonanalogous art, it has been held that a prior art reference must either be in the field of the inventor’s endeavor or, if not, then be reasonably pertinent to the particular problem with which the inventor was concerned, in order to be relied upon as a basis for rejection of the claimed invention. See In re Oetiker, 977 F.2d 1443, 24 USPQ2d 1443 (Fed. Cir. 1992). In this case, both the cited art of Saxena and applicant’s claimed invention are both in the field of messages over telecommunication lines comprising different formats and whereby said messages are converted into claimed schema. This is a broad field of endeavor and as such encompasses a plurality of technologies that address input messages. Saxena in Fig. 9 and paragraphs [0038], [0039] [0049] [0098], [0125], [0143] and several other paragraphs details such messages and how they are grouped in to keys and pairs.
Upon further consideration new grounds of rejection have been necessitated due
to Applicant's amendments and are made in view of Sentell et al., (United States Patent Publication Number 2017/0103171) hereinafter Sentell
Claim Rejections – 35 U.S.C. §103
5. 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.
6. The factual inquiries set forth in Graham v John Deere Co., 383 U.S. 1, 148 USPQ
459 (1966), that are applied for establishing a background for determining obviousness
under 35 U.S.C. 103 are summarized as follows:
a. Determining the scope and contents of the prior art
b. Ascertaining the differences between the prior art and the claims at issue
c. Resolving the level of ordinary skill in the pertinent art
d. Considering objective evidence present in the application indicating
obviousness or nonobviousness
Claims 1 – 13 and 15 - 19 are rejected under 35 U.S.C. 103 as being unpatentable Saxena et al. (United States Patent Publication Number 2021/0374153), hereinafter Saxena in view of Sentell et al., (United States Patent Publication Number 2017/0103171) hereinafter Sentell.
Regarding claim 1 Saxena teaches a system for managing entity life information; (a system [0016]) comprising: one or more processors or microprocessors (a processor [0016]) in electronic communication (monitored communication [0092]) with at least one database (Fig. 1, (110) logs database [0041]) on a memory storage device, (a memory [0016]) wherein the one or more processors or microprocessors (a processor [0016]) are programmed to: (configured to perform a task [0016]) receive, (received [0054]) over a telecommunications network, (over a network (such as the Internet, a local network, or any other type of network, as appropriate) [0038]) data input messages (log messages and metrics [0038]) such as “data input messages” containing entity care information (customer information [0151]) such as “entity care information” from one or more data sources, (_sourceCategory=aws/cloudtrail [0157]) [0060]) wherein at least a portion of the data input messages (log messages and metrics [0038]) such as “data input messages” are in different types and /or formats (such as JSON (JavaScript Object Notation) for logging. [0019]) and further wherein said entity comprises one or more of an animal, a person, (customer [0102]) a vehicle, a book, a manuscript, an item of furniture, or a piece or work of art; convert (to extract values in the structured data, various parsers may be applied ( e.g., JSON, CSV, delimiter, key-value, xml, etc.) to convert each log into the structured key-value map representation. [0290]) into a payload manifest schema (ABS. key schema) (Fig. 3, (306) key schema [0174]) comprising one or more observables, (One column contains a comma separated list of the keys of the flattened object up to a user-specified depth in lexicographic order. Another column contains the hash of the list of keys. This hash value is consistent across logs which have the same schema and can be used to filter out the logs with the same schema [0047]) said observables comprising discrete data key-value pairs (“LogReduce Keys” [0057]; “LogReduce Values” [0058]) matching parsed data from the data input message (parsed out [0130]) to semantic ontology definitions; (the portion of the raw log data with the structured data of interest is parsed out ( e.g., using an appropriate parser). [0054]) transform (the platform applies upstream parsers/transformations to arrive at a final representation that is a structured mapping of keys to values. For example, a JSON parse could be performed to determine that a JSON field is CSV. They are then sequenced and pipelined, and the JSON is parsed out. [0089]) the payload manifest schema (ABS. key schema) (Fig. 3, (306) key schema [0174]) to a curated manifest, (JSON schema [0073]) such as “curated manifest” said curated manifest (JSON schema [0073]) such as “curated manifest” comprising a multi-JSON semantic normalized representation (for example, logs as rows and JSON keys as columns. [0028]) of select entity care data; (customer information [0151]) such as “entity care information” and send (logs in the cluster that have the same JSON schema [0073]) the curated manifest (JSON schema [0073]) such as “curated manifest” for storage in said at least one database (Fig. 1, (110) stored to logs database 110 [0041])
Saxena does not fully disclose an animal or a person and said entity care information comprises health care information about said animal or person
Sentell teaches an animal or a person (patient [0038], [0053]) and said entity care information (Prior health-care activity, claims data, insurance data may be accessed [0023]) such as “entity care information” comprises health care information (Figs. 3, 4, 5A and 6 – 10 healthcare information [0009], [0010], [0011], [0013] – [0017]) about said animal or person (patient [0038], [0053])
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Saxena in view of Hosseini to incorporate the teachings of Sentell wherein an animal or a person and said entity care information comprises health care information about said animal or person. By doing so enable consumers to make more-fully informed choices regarding their health plans, providers, and treatments. [0023]
Regarding claim 2 Saxena in view of Sentell teaches the system of claim 1,
Saxena further teaches wherein the curated manifest (JSON schema [0073]) such as “curated manifest” is immutable (For example, JSON logs are becoming increasingly common, such as for modem applications that run natively on public clouds. However, such log data already has a structure imposed at write time, [0019]) such as “immutable”
Regarding claim 3 Saxena in view of Sentell teaches the system of claim 1,
Saxena further teaches wherein there is a single curated manifest (JSON schema [0073]) such as “curated manifest” created from a single data input message. (logs with the same JSON schema/belonging to the same cluster [0047])
Regarding claim 4 Saxena in view of Sentell teaches the system of claim 1,
Saxena further teaches wherein the curated manifest (JSON schema [0073]) such as “curated manifest” has a structure comprising a header section, an actor section, an item section, and an observation section, (various metadata [0054]) such as “header section, an actor section, an item section, and an observation section”
Regarding claim 5 Saxena in view of Sentell teaches the system of claim 4,
Saxena further teaches wherein the one or more processors or microprocessors (a processor [0016]) are programmed to create (configured to perform a task [0016]) such as “create” an observation component (test set [0098]) such as “observation component” for each observable data key-value pair, (key-value pairs [0098]) create an observation (an explanation [0098]) such as “observation” by grouping one or more observation components, (group of logs (also referred to herein as the test set) [0098]) such as “observation components” and add the observation (an explanation [0098]) such as “observation” to the observation section (accommodate any type of structured data as appropriate. [0089] such as “observation section” of the manifest. (JSON schema [0073]) such as “curated manifest”
Regarding claim 6 Saxena in view of Sentell teaches the system of claim 5,
Saxena further teaches wherein the one or more processors or microprocessors (a processor [0016]) are programmed to identify (configured to perform a task [0016]) such as “identify” one or more actors (actor [0088]) in actor-related observations, (potentially strange behaviors of items that are entities that are occurring in the system [0088]) perform an identity matching process to identity an entity (the user can direct the structured log analysis platform to determine patterns of behaviors in those components … and can determine any associations or relations between what they are doing and how they are doing [0088]) corresponding to said one or more actors, (actor [0088]) and enter actor (actor [0088]) and entity data (Customer IDs and Caller Module Keys and their values [0088]) such as “entity data” in the actor section (accommodate any type of structured data as appropriate. [0089] such as “actor section” of the curated manifest (JSON schema [0073]) such as “curated manifest”
Regarding claim 7 Saxena in view of Sentell teaches the system of claim 5,
Saxena further teaches wherein the one or more processors or microprocessors (a processor [0016]) are programmed to identify (configured to perform a task [0016]) such as “identify” one or more items in item-related observations, (the operators have been used to extract potentially strange behaviors of items that are entities that are occurring in the system [0088]) and enter item data (item set mining is used in facilitating the determining of whether a subset of key-values is overrepresented in the test set versus the control set [0107]) such as “item data” in the item section (accommodate any type of structured data as appropriate. [0089] such as “item section” of the curated manifest (JSON schema [0073]) such as “curated manifest”
Regarding claim 8 Saxena in view of Sentell teaches the system of claim 1,
Saxena further teaches, wherein the one or more processors or microprocessors(a processor [0016]) are programmed to receive, (configured to perform a task [0016]) such as “receive” over a telecommunications network, (over a network (such as the Internet, a local network, or any other type of network, as appropriate) [0038]) a data request, (query of structured log data [0024]) and to provide a contextually best record view (summarized view with the different key schemas prioritized for example according to the count of the number of logs or prioritized according to the unique key schema [0068]) such as “contextually best record view” from the best data (inliers [0124]) such as “best data” in one or more curated manifests (JSON schema [0073]) such as “curated manifest” responsive to the data request, (query of structured log data [0024]) wherein the best data (inliers [0124]) such as “best data” is determined from contextual criteria (to gain insight [0042]) based on the requested context (performing queries (e.g., customer query 112) [0042])
Regarding claim 9 Saxena in view of Sentell teaches the system of claim 8,
Saxena further teaches wherein contextual criteria (to gain insight [0042]) comprises data source (For example, they may be applied to JSON (or CSV) log sources. They may also be applied to various other types of structured log sources. Other examples of structured log sources include key-value formatted logs, XML-formatted logs, etc. [0060])
Regarding claim 10 Saxena in view of Sentell teaches the system of claim 8,
Saxena further teaches wherein contextual criteria (to gain insight [0042]) comprises data status (the user may specify some test predicate which can be applied to each row/log (e.g., "isFailed==true"), where this test predicate is used to partition the dataset into disjoint test and control sets [0035)
Regarding claim 11 Saxena in view of Sentell teaches the system of claim 8,
Saxena further teaches wherein the contextually best record view (summarized view with the different key schemas prioritized for example according to the count of the number of logs or prioritized according to the unique key schema [0068]) such as “contextually best record view” is created on demand (based on the execution of the operator and presented to the user through the UI [0052]) such as “on demand”
Regarding claim 12 Saxena in view of Sentell teaches the system of claim 8,
Saxena further teaches wherein the contextually best record view (summarized view with the different key schemas prioritized for example according to the count of the number of logs or prioritized according to the unique key schema [0068]) such as “contextually best record view” is a previously- created persisted contextually best record view (“inputSchema” [0161]) such as “previously-created persisted contextually best record view”
Regarding claim 13 Saxena in view of Sentell teaches the system of claim 12,
Saxena further teaches, wherein the persisted contextually best record view (“inputSchema” [0161]) is updated in real-time as curated manifests are created (this schema may be updated by some operators, and may be fed from one operator to another in a search pipeline [0161])
Regarding claim 15 Saxena teaches a method (clustering method [0259]) for managing entity life information; comprising: one or more processors or microprocessors (a processor [0016]) in electronic communication with at least one database (Fig. 1, (110) logs database [0041]) on a memory storage device, (a memory [0016]) wherein the one or more processors or microprocessors (a processor [0016]) are programmed to: (configured to perform a task [0016]) receiving, (received [0054]) by one or more processors or microprocessors (a processor [0016]) in electronic communication with at least one database (Fig. 1, (110) logs database [0041]) on a memory storage device, (a memory [0016]) over a telecommunications network, (over a network (such as the Internet, a local network, or any other type of network, as appropriate) [0038]) containing entity care information (JSON data [0054]) such as “entity care information from one or more data sources, (_sourceCategory=aws/cloudtrail [0157]) [0060]) wherein at least a portion of the data input messages (log messages and metrics [0038]) such as “data input messages” are in different types and /or formats (such as JSON (JavaScript Object Notation) for logging. [0019]) and further wherein said entity comprises one or more of an animal, a person, (customer [0102]) a vehicle, a book, a manuscript, an item of furniture, or a piece or work of art; converting (to extract values in the structured data, various parsers may be applied ( e.g., JSON, CSV, delimiter, key-value, xml, etc.) to convert each log into the structured key-value map representation. [0290]) into a payload manifest schema (ABS. key schema) (Fig. 3, (306) key schema [0174]) comprising one or more observables, (One column contains a comma separated list of the keys of the flattened object up to a user-specified depth in lexicographic order. Another column contains the hash of the list of keys. This hash value is consistent across logs which have the same schema and can be used to filter out the logs with the same schema [0047]) said observables comprising discrete data key-value pairs (“LogReduce Keys” [0057]; “LogReduce Values” [0058]) matching parsed data from the data input message (parsed out [0130]) to semantic ontology definitions; (the portion of the raw log data with the structured data of interest is parsed out ( e.g., using an appropriate parser). [0054]) transforming (the platform applies upstream parsers/transformations to arrive at a final representation that is a structured mapping of keys to values. For example, a JSON parse could be performed to determine that a JSON field is CSV. They are then sequenced and pipelined, and the JSON is parsed out. [0089]) the payload manifest schema (ABS. key schema) (Fig. 3, (306) key schema [0174]) to a curated manifest, (JSON schema [0073]) such as “curated manifest said curated manifest(JSON schema [0073]) such as “curated manifest” comprising a multi-JSON semantic normalized representation (for example, logs as rows and JSON keys as columns. [0028]) of select entity care data; (JSON data [0054]) such as “entity care information” and sending (logs in the cluster that have the same JSON schema [0073]) the curated manifest (JSON schema [0073]) such as “curated manifest” for storage in said at least one database (Fig. 1, (110) stored to logs database 110 [0041])
Saxena does not fully disclose an animal or a person and said entity care information comprises health care information about said animal or person
Sentell teaches an animal or a person (patient [0038], [0053]) and said entity care information (Prior health-care activity, claims data, insurance data may be accessed [0023]) such as “entity care information” comprises health care information (Figs. 3, 4, 5A and 6 – 10 healthcare information [0009], [0010], [0011], [0013] – [0017]) about said animal or person (patient [0038], [0053])
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Saxena in view of Hosseini to incorporate the teachings of Sentell wherein an animal or a person and said entity care information comprises health care information about said animal or person. By doing so enable consumers to make more-fully informed choices regarding their health plans, providers, and treatments. [0023]
Regarding claim 16 Saxena in view of Sentell teaches the method (clustering method [0259]) of claim 15,
Saxena further teaches wherein the curated manifest(JSON schema [0073]) such as “curated manifest” is immutable, (For example, JSON logs are becoming increasingly common, such as for modem applications that run natively on public clouds. However, such log data already has a structure imposed at write time, [0019]) such as “immutable” and there is a single curated manifest created from a single data input message. (logs with the same JSON schema/belonging to the same cluster [0047])
Regarding claim 17 Saxena in view of Sentell teaches the method (clustering method [0259]) of claim 15,
Saxena further teaches wherein the curated manifest has a structure comprising a header section, an actor section, an item section, and an observation section, (various metadata [0054]) such as “header section, an actor section, an item section, and an observation section” and further comprising the steps of: creating (configured to perform a task [0016]) such as “create” an observation component (test set [0098]) such as “observation component” for each observable data key-value pair, (key-value pairs [0098]) create an observation (an explanation [0098]) such as “observation” by grouping one or more observation components; (group of logs (also referred to herein as the test set) [0098]) such as “observation components” adding the observation (an explanation [0098]) to the observation section (accommodate any type of structured data as appropriate. [0089] such as “observation section” of the manifest; (JSON schema [0073]) such as “curated manifest” identifying (configured to perform a task [0016]) such as “identify” one or more actors (actor [0088]) in actor-related observations; (potentially strange behaviors of items that are entities that are occurring in the system [0088]) performing an identity matching process to identity an entity (the user can direct the structured log analysis platform to determine patterns of behaviors in those components … and can determine any associations or relations between what they are doing and how they are doing [0088]) corresponding to said one or more actors; (actor [0088]) entering actor (actor [0088]) and entity data (Customer IDs and Caller Module Keys and their values [0088]) such as “entity data” in the actor section (accommodate any type of structured data as appropriate. [0089] such as “actor section” of the curated manifest; (JSON schema [0073]) such as “curated manifest” identifying (configured to perform a task [0016]) such as “identify one or more items in item-related observations, (the operators have been used to extract potentially strange behaviors of items that are entities that are occurring in the system [0088]) and entering item data (item set mining is used in facilitating the determining of whether a subset of key-values is overrepresented in the test set versus the control set [0107]) such as “item data” in the item section (accommodate any type of structured data as appropriate. [0089] such as “item section” of the curated manifest (JSON schema [0073]) such as “curated manifest”
Regarding claim 18 Saxena in view of Sentell teaches the method (clustering method [0259]) of claim 15,
Saxena further teaches comprising the steps of: receiving, (configured to perform a task [0016]) such as “receive over a telecommunications network, (over a network (such as the Internet, a local network, or any other type of network, as appropriate) [0038]) a data request; (query of structured log data [0024]) and providing a contextually best record view (summarized view with the different key schemas prioritized for example according to the count of the number of logs or prioritized according to the unique key schema [0068]) such as “contextually best record view” from the best data (inliers [0124]) such as “best data” in one or more curated manifests (JSON schema [0073]) such as “curated manifest” responsive to the data request; (query of structured log data [0024]) wherein the best data (inliers [0124]) such as “best data” is determined from contextual criteria (to gain insight [0042]) based on the requested context, (performing queries (e.g., customer query 112) [0042]) said contextual criteria (to gain insight [0042]) comprising data source (For example, they may be applied to JSON (or CSV) log sources. They may also be applied to various other types of structured log sources. Other examples of structured log sources include key-value formatted logs, XML-formatted logs, etc. [0060]) and/or data status. (the user may specify some test predicate which can be applied to each row/log (e.g., "isFailed==true"), where this test predicate is used to partition the dataset into disjoint test and control sets [0035)
Regarding claim 19 Saxena in view of Sentell teaches the method (clustering method [0259]) of claim 15,
Saxena further teaches wherein the contextually best record view (summarized view with the different key schemas prioritized for example according to the count of the number of logs or prioritized according to the unique key schema [0068]) such as “contextually best record view” is a previously- created persisted contextually best record view (“inputSchema” [0161]) such as “previously-created persisted contextually best record view” updated in real-time as curated manifests are created. (this schema may be updated by some operators, and may be fed from one operator to another in a search pipeline [0161])
Claims 14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable Saxena et al. (United States Patent Publication Number 2021/0374153), hereinafter Saxena in view of Sentell et al., (United States Patent Publication Number 2017/0103171) hereinafter Sentell and in further view of Ostrovsky et al. (United States Patent Publication Number 20190087316), hereinafter referred to as Ostrovsky.
Regarding claim 14 Saxena in view of Sentell teaches the system (a system [0016]) of claim 1,
Saxena further teaches wherein the receive function, (received [0054]) convert function, (to extract values in the structured data, various parsers may be applied ( e.g., JSON, CSV, delimiter, key-value, xml, etc.) to convert each log into the structured key-value map representation. [0290]) and transform function (the platform applies upstream parsers/transformations to arrive at a final representation that is a structured mapping of keys to values. For example, a JSON parse could be performed to determine that a JSON field is CSV. They are then sequenced and pipelined, and the JSON is parsed out. [0089]) are carried out with multiple process threads, (thread=MTP-RawOutput-Processor-Session [0179], [0180], [0181])
Saxena does not fully disclose wherein each thread corresponds to a specific function, and multiple functions can run simultaneously
Ostrovsky teaches wherein each thread (Figs. 2 – 4 Thread 1, Thread 2 and Thread 3 [0011], [0012], [0013]; two or more threads [0026]) corresponds to a specific function, (Each process provides the resources to execute the program. One or more threads run in the context of the process … The thread is the entity within a process that can be scheduled for execution [0021]) and multiple functions can run simultaneously (In parallel applications, threads can be concurrently executed on the processor 102. [0022])
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Saxena in view of Hosseini to incorporate the teachings of Ostrovsky wherein each thread corresponds to a specific function, and multiple functions can run simultaneously. By doing so concurrent programming for shared-memory multiprocessors can include the ability for multiple threads to access the same data. Ostrovsky [0022]
Regarding claim 20 Saxena in view of Sentell teaches the method (clustering method [0259]) of claim 15,
Saxena further teaches wherein the process steps of receiving, (received [0054]) converting, (to extract values in the structured data, various parsers may be applied ( e.g., JSON, CSV, delimiter, key-value, xml, etc.) to convert each log into the structured key-value map representation. [0290]) and transforming (the platform applies upstream parsers/transformations to arrive at a final representation that is a structured mapping of keys to values. For example, a JSON parse could be performed to determine that a JSON field is CSV. They are then sequenced and pipelined, and the JSON is parsed out. [0089]) are carried out with multiple process threads, (thread=MTP-RawOutput-Processor-Session [0179], [0180], [0181])
Saxena does not fully disclose wherein each thread corresponds to a specific process, and multiple processes can run simultaneously
Ostrovsky teaches wherein each thread (Figs. 2 – 4 Thread 1, Thread 2 and Thread 3 [0011], [0012], [0013]; two or more threads [0026]) corresponds to a specific process, (Each process provides the resources to execute the program. One or more threads run in the context of the process … The thread is the entity within a process that can be scheduled for execution [0021]) and multiple processes can run simultaneously (In parallel applications, threads can be concurrently executed on the processor 102. [0022])
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Saxena in view of Hossieni to incorporate the teachings of Ostrovsky wherein each thread corresponds to a specific function, and multiple functions can run simultaneously. By doing so concurrent programming for shared-memory multiprocessors can include the ability for multiple threads to access the same data. Ostrovsky [0022]
Conclusion
7. The prior art made of record and not relied upon is considered pertinent to
applicant's disclosure.
Steinberg et al., (United States Patent Publication Number 20050149359) teaches “health care information is received for a plurality of patients. This patient information can be received from many different sources as well, as will be apparent to one having skill in the art. In accordance with an embodiment of the present invention, these sources could include records from an insurance company or program sponsor, or from individual patients through biometric data sent over a telephone line, or clinical data reported by physicians for example. The health care information can be analyzed to determine health care options that may have a tendency to reduce future health care costs for individual patients, or improve the quality of care for the patient [0019]”
8. Any inquiry concerning this communication or earlier communications from the
examiner should be directed to Kweku Halm whose telephone number is (469) 295-
9144. The examiner can normally be reached on 7:30AM - 5:30PM Mon - Thur. If
attempts to reach the examiner by telephone are unsuccessful, the examiner's
supervisor, Sanjiv Shah can be reached on (571) 272-4098. The fax phone
number for the organization where this application or proceeding is assigned is 571-273-
8300.
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/KWEKU WILLIAM HALM/Examiner, Art Unit 2166
/SANJIV SHAH/Supervisory Patent Examiner, Art Unit 2166