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 .
Status of Claims
The office action is being examined in response to the application filed by the applicant on 3 March 2025.
Claims 1-14 are pending and have been examined.
This action is made NON-FINAL.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 5 and 7 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “relatively large negative post count” in claim 5 is a relative term which renders the claim indefinite. The term “relatively large negative post count” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The claim does not recite a quantifiable way to measure what a relatively large count means. That is, relatively large count of negative posts is a relative term that is recited without measurable standard for determining the limits or boundary conditions, such that a person having ordinary skill in the art would not be apprised of the scope for ascertaining the requisite degree of a count that is “relatively” large.
The term “comprehensively relevant” post data about services in claim 7 is a relative term which renders the claim indefinite. The term “comprehensively relevant” post data about services is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The claim does not recite a quantifiable way to measure what a “comprehensively relevant” post data about services means. That is, “comprehensively relevant” post data about services is a relative term that is recited without measurable standard for determining the limits or boundary conditions, such that a person having ordinary skill in the art would not be apprised of the scope for ascertaining the requisite degree of comprehensively relevant data for the services.
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 therefore, subject to the conditions and requirements of this title.
Claim 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claims
Regarding Claims 1 and 13 and 14: The claims recite: identify service data from post, execute sentiment analysis on each post, detect anomaly based on each service identified and the sentiment results for each post or portion of a post. These limitations, the identify, execute, and detect functions, are all abstract ideas in the categories of "Certain Methods of Organizing Human Activity" in the subcategory of Managing Personal Behavior or Relationships or Interactions Between People: including tracking social activities on social media, and in the sub-category of commercial interactions: including advertising and marketing activities or behaviors, and business relations. Additionally, these functions are in the certain methods of organizing human activity category in the sub-category of managing personal behavior or relationships or interactions between people because they recite a mental process that was historically performed by a human that is searching for relevant data that discloses information relative to a business, in order to identify, determine the sentiment, and detect anomalies based on the identified data and sentiment of the post.
The claims do not recite limits to how the data manipulations are performed or limits to the mechanism that is to perform these functions. Therefore, it would be reasonable for a person having ordinary skill in the art to interpret that each of the claim limitations are performed as mental processes, based on the broadest reasonable interpretation of the plain English meaning of the claim language.
Insofar as the claims recite acquire messaging data, the specification does not reveal advances in collecting, sending, receiving, or displaying data.
The additional elements recited in claims 1 and 14 is the processor, and in claim 14, a non-transitory computer readable medium (CRM) storing a program that causes a computer to perform the program. In the system claims, these elements, i.e. the processor and CRM causing a computer to perform, are general-purpose general-purpose computing structures, implementing software, recited at a high level of generality. That is, for claims 1 and 13, the general-purpose computing structures are applied as tools to implement the abstract ideas, i.e. “apply it.” For claim 13, i.e. the method claim, there are no additional elements.
The specification is focused on the nature of the data being manipulated - i.e. the descriptive nature of the data. Manipulating characterized data into alternately characterized data is not a transformation, i.e. data is data. The claims are merely executing the instructions recited in the claims, and in claims 1 and 14, executing said instructions via general-purpose computing structures, that are all incidental or token additions to the claim. That is, the computing structures do not alter how the steps of the claims are performed. For these system claims, 1 and 14, the data is merely input into and returned from these structures, without detailing what occurs in between. For claim 13, the claims merely execute instructions, where data is input and returned, without detailing the mechanism that might perform the functions, i.e. there are no structures recited in the claim at all. Therefore, claims 1, 13, and 14, are no more than a drafting effort designed to monopolize the abstract ideas. That is, the judicial exceptions are not applied or used in some other meaningful way beyond being generally linked and applied using the additional elements as tools, in claims 1 and 14.
Practical Application: The claims as a whole, while looking at the additional elements individually and as a combination, do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea.
Significantly more: This analysis for significantly more is commensurate with the analysis above. For the same reasons disclosed above, the additional elements, only found in claims 1 and 14, that do not integrate the judicial exception into a practical application in these claims, when taken individually and in combination, also do not result in the claims 1 and 14, as a whole, amounting to significantly more than the identified abstract idea. The claims, 1, 13, and 14, are directed to an abstract idea without significantly more.
Dependent Claims
Regarding Claim 2: Insofar as the claim recites: identify data based on posts and a vocabulary database, these limitations further add to the abstract ideas from the independent claim. The same analyses apply, i.e. the claims place no limits on how the functions are performed or on the mechanism that is implemented to do the performing. The claim recites the same system with a processor as identified in claim 1 as the additional element. This general-purpose computing structure is recited at a high level of generality. Said computing structure is merely applied as a tool to perform the claimed instructions without revealing advances to computing structures in the specification. Therefore, the additional element is not indicative of integrating the abstract idea into a practical application and does not amount to significantly more than the abstract idea.
Regarding claim 3: Insofar as the claim recites: determine if data includes a negative expression to execute sentiment analysis on and calculate a negative post count with negative expression to detect the anomaly for a service, these limitations further add to the abstract ideas from the independent claim. The same analyses apply, i.e. the claims place no limits on how the functions are performed or on the mechanism that is implemented to do the performing. This general-purpose computing structure is recited at a high level of generality. Said computing structure is merely applied as a tool to perform the claimed instructions without revealing advances to computing structures in the specification. Therefore, the additional element is not indicative of integrating the abstract idea into a practical application and does not amount to significantly more than the abstract idea.
Regarding Claims 4 -6: Insofar as the claims recite: In each claim, depending from claim 3, to detect the anomaly: in claim 4: of each service based on a time series change in the negative post count ; in claim 5: relating to a service configuration having a relatively large post count; and in claim 6: relating to a common service configuration when the negative post count is equal to or larger than a threshold, these limitations further add to the abstract ideas from the independent claim. The same analyses apply, i.e. the claims place no limits on how the functions are performed or on the mechanism that is implemented to do the performing. The claims recite the same additional elements as claim 1, the system with a processor.This general-purpose computing structure is recited at a high level of generality. Said computing structure is merely applied as a tool to perform the claimed instructions without revealing advances to computing structures in the specification. Therefore, the additional element is not indicative of integrating the abstract idea into a practical application and does not amount to significantly more than the abstract idea.
Regarding Claims 7 and 9: Insofar as the claims recite: In each claim, where claim 7 depends from claim 1 and claim 9 depends from claim 8, identify data and detect the anomaly. Claim 7 further limits the identify limitation to identify comprehensively relevant post data to a service, and claim 9 further limits the identify limitation to identify, from state data, data relevant to the post and service. Claim 7 further limits the detect limitation to detect, from the post data, the service anomaly for each service; Claim 9 further limits the detect limitation to detect, from the service relevant state and post data, the anomaly. These limitations further add to the abstract ideas from the independent claim. The same analyses apply, i.e. the claims place no limits on how the functions are performed or on the mechanism that is implemented to do the performing. The claims recite the same additional elements as claim 1, the system with a processor. This general-purpose computing structure is recited at a high level of generality. Said computing structure is merely applied as a tool to perform the claimed instructions without revealing advances to computing structures in the specification. Therefore, the additional element is not indicative of integrating the abstract idea into a practical application and does not amount to significantly more than the abstract idea.
Regarding Claims 8, and 10-12: Insofar as the claims recite: In each claim, where each claim depends from claim 1, acquire and detect the anomaly. Claim 8 further limits the acquire limitation to acquire state data for state of system used device, and limits the detect limitation to detect the anomaly relating to said state data on each of the services. Claim 10 further limits the acquire limitation to acquire specialty word information relating to post data, and detects the anomaly of each service based on the specialty words in the posts. Claim 11 further limits the acquire limitation to acquire campaign information for the services, and limits the detect limitation to detect the anomaly based on the campaign information. Claim 12 limits the acquire limitation to acquire distribution content in a distribution service for distribution information, and the detect limitation to detect the anomaly of each service based on the distribution content. These limitations further add to the same acquire and detect limitation abstract ideas from the independent claim. The same analyses apply, i.e. the claims place no limits on how the functions are performed or on the mechanism that is implemented to do the performing. The claims recite the same additional elements as claim 1, the system with a processor. This general-purpose computing structure is recited at a high level of generality. Said computing structure is merely applied as a tool to perform the claimed instructions without revealing advances to computing structures in the specification. Therefore, the additional element is not indicative of integrating the abstract idea into a practical application and does not amount to significantly more than the abstract idea.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Gonzalaz Macias, US20220342745A1, hereinafter “Gonzalaz.”
[Claims 1, 13, and 14] Gonzalaz discloses: An anomaly detection system, comprising at least one processor configured to: acquire each of a plurality of pieces of post data in a social networking service (SNS); [0021] (processor is configured to perform the functions based on the instructions), [0003] (receive social media messages);
identify a post-relevant service that is relevant to each of the plurality of pieces of post data out of a plurality of services being targets of anomaly detection; [0003] “an anomaly may indicate… number of people having issues with a computing system, software application, website, or other service. The text from one or more social media messages associated with a detected anomaly may indicate what service, component, device, etc. is having a problem;”
execute sentiment analysis for each of the plurality of pieces of post data; and [0003] “may include an anomaly detection service and/or a sentiment analysis service for analyzing the social media messages.”
detect an anomaly relating to each of the plurality of services based on the post- relevant service identified for the each of the plurality of pieces of post data and a result of the sentiment analysis executed for the each of the plurality of pieces of post data. [0003] “an anomaly may indicate that …. number of people having issues with a computing system, software application, website, or other service. The text from one or more social media messages associated with a detected anomaly may indicate what service, component, device, etc. is having a problem … may include an anomaly detection service and/or a sentiment analysis service for analyzing the social media messages.”
[Claim 2] Gonzalaz discloses: The anomaly detection system according to claim 1, wherein at least one processor is configured to identify, based on each of the plurality of pieces of post data and a dictionary database in which a word specific to each of the plurality of services is registered, the post-relevant service of the each of the plurality of pieces of post data. [0021] (processor is configured to perform the functions based on the instructions), [0040-0041] (detect anomalies based on keywords associated with each of the plurality of the specific processes or services, such that the system compares the words in the text messages to the keywords associated with the plurality of services), [0044] (the keywords are stored in a set of keywords, i.e. a dictionary, and are associated with a particular service; only the services that subscribe are serviced in this manner, i.e. the disclosure may specifically disclose a first and a second service in latter [0075] disclosing claim embodiments at the time of publication. However, the disclosure appears to simplify the data by only detailing a first and second service, without setting forth actual limits to the number of services that may subscribe and therefore be subject to this prior art disclosure), [0020] “use anomaly detection in social media messages or other communication channels both internal or external.”
[Claim 3] Gonzalaz discloses: The anomaly detection system according to claim 1: wherein at least one processor is configured to determine whether each of the plurality of pieces of post data includes a negative expression, to thereby execute the sentiment analysis for the each of the plurality of pieces of post data, and [0021] (processor is configured to perform the functions based on the instructions), [0016] (determine negative expressions in each of the messages from the plurality of messages, through executing sentiment analyses of the messages);
wherein at least one processor is configured to calculate, for each of the plurality of services, a negative post count being the number of pieces of post data including the negative expression, and to detect the anomaly of each of the plurality of services based on the negative post count of the each of the plurality of services. [0021] (processor is configured to perform the functions based on the instructions), (count each social media sentiment identifier, i.e. count the negative expression messages each from the plurality of messages).
[Claim 4] Gonzalaz discloses: The anomaly detection system according to claim 3, wherein at least one processor is configured to detect the anomaly of each of the plurality of services based on a time-series change in the negative post count of the each of the plurality of services. [0021] (processor is configured to perform the functions based on the instructions), [0032] (count each social media sentiment identifier, i.e. count the negative expression messages each from the plurality of messages; the detection of the counts are performed based on a time series change).
[Claim 5] Gonzalaz discloses: The anomaly detection system according to claim 3, wherein at least one processor is configured to detect the anomaly relating to a configuration specific to a service having a relatively large negative post count out of the plurality of services. [0021] (processor is configured to perform the functions based on the instructions), [0041] (determine if the anomaly is relative to the software or hardware configurations), [0032] (unusually large count of sentiment identifiers).
[Claim 6] Gonzalaz discloses: The anomaly detection system according to claim 3, wherein at least one processor is configured to detect the anomaly relating to a configuration common to the plurality of services when the negative post count of each of the plurality of services is equal to or larger than a threshold value. [0021] (processor is configured to perform the functions based on the instructions), [0032] (the count is larger than a threshold), [0041] (determine if the anomaly is relative to the software or hardware configurations).
[Claim 7] Gonzalaz discloses: The anomaly detection system according to claim 1, wherein at least one processor is configured to identity post data comprehensively relevant to the plurality of services based on each of the plurality of pieces of post data, [0021] (processor is configured to perform the functions based on the instructions), [0032] (count each social media sentiment identifier), [0040-0041] (detect anomalies associated with each of the plurality of the specific processes or services from the post data, i.e. the post data is comprehensively relevant to the services);
wherein the at least one processor is configured to detect the anomaly relating to each of the plurality of services based further on the post data. [0021] (processor is configured to perform the functions based on the instructions), [0032] (count each social media sentiment identifier), [0040-0041] (detect anomalies associated with each of the plurality of the specific processes or services from the post data, i.e. the post data is comprehensively relevant to the services),
[Claim 8] Gonzalaz discloses: The anomaly detection system according to claim 1,
wherein at least one processor configured to acquire state data relating to a state of a device used in each of the plurality of services, and [0021] (processor is configured to perform the functions based on the instructions), [0003] “an anomaly may indicate that there is an unusually large number of people having issues with a computing system, software application, website, or other service. The text from one or more social media messages associated with a detected anomaly may indicate what service, component, device, etc. is having a problem.”
wherein the at least one processor is configured to detect the anomaly relating to each of the plurality of services based further on the state data on each of the plurality of services. [0021] (processor is configured to perform the functions based on the instructions), [0003] “an anomaly may indicate that there is an unusually large number of people having issues with a computing system, software application, website, or other service. The text from one or more social media messages associated with a detected anomaly may indicate what service, component, device, etc. is having a problem.”
[Claim 9] Gonzalaz discloses: The anomaly detection system according to claim 8, wherein at least one processor configured to identify, out of a plurality of pieces of the state data on each of the plurality of services, relevant data relevant to the post data the identified post-relevant service of which is a corresponding one of the plurality of services, [0021] (processor is configured to perform the functions based on the instructions), [0003] “an anomaly may indicate that there is an unusually large number of people having issues with a computing system, software application, website, or other service. The text from one or more social media messages associated with a detected anomaly may indicate what service, component, device, etc. is having a problem.”
wherein at least one processor is configured to detect, based on, out of the plurality of pieces of the state data on each of the plurality of services, the relevant data on the corresponding one of the plurality of services, the anomaly of the corresponding one of the plurality of services. [0021] (processor is configured to perform the functions based on the instructions), [0020] “may include one or more computing devices configured to monitor other computing systems or computing devices,” [0020] “use anomaly detection in social media messages or other communication channels both internal or external to detect issues or malfunctions in one or more computing systems (e.g., computing systems that are monitored by the monitoring platform 106).”
[Claim 10] Gonzalaz discloses: The anomaly detection system according to claim 1 wherein at least one processor configured to acquire specialty information relating to specialty of a word included in each of the plurality of pieces of post data, [0021] (processor is configured to perform the functions based on the instructions), [0040-0041] (detect anomalies based on keywords associated with each of the plurality of the specific processes or services, such that the system compares the words in the text messages to the keywords associated with the plurality of services, i.e. specialty information relating to the specialty of a word), [0044] (the keywords are stored in a set of keywords, i.e. a dictionary, and are associated with a particular service; only the services that subscribe are serviced in this manner), [0020] “use anomaly detection in social media messages or other communication channels both internal or external.”
wherein at least one processor is configured to detect the anomaly of each of the plurality of services based further on the specialty information on the each of the plurality of pieces of post data. [0021] (processor is configured to perform the functions based on the instructions), [0040-0041] (detect anomalies based on keywords associated with each of the plurality of the specific processes or services, such that the system compares the words in the text messages to the keywords associated with the plurality of services, i.e. specialty information relating to the specialty of a word), [0044] (the keywords are stored in a set of keywords, i.e. a dictionary, and are associated with a particular service; only the services that subscribe are serviced in this manner), [0020] “use anomaly detection in social media messages or other communication channels both internal or external.”
[Claim 11] Gonzalaz discloses: The anomaly detection system according to claim 1: wherein at least one processor is configured to acquire campaign information relating to a campaign in each of the plurality of services, [0021] (processor is configured to perform the functions based on the instructions, send and receive commands, requests, and other suitable data using the I/O paths), [0026] “may request particular types of social media messages from the social media platform…may request social media messages that mention or otherwise indicate a particular entity (e.g., the organization, user, company, group, etc. that is associated with the anomaly detection system 102) … may subscribe to particular types of social media messages (e.g., messages that mention or otherwise correspond to a particular entity),” (i.e. configured to acquire a campaign of information, in this case, messages that mention or indicate a particular entity);
wherein at least one processor is configured to detect the anomaly of each of the plurality of services based further on the campaign information. [0021] (processor is configured to perform the functions based on the instructions), [0026] “Social media messages that mention or otherwise indicate the entity associated with the anomaly detection system 102 may be useful in determining whether an anomaly has occurred (e.g., whether an application of the entity is not working correctly, something the entity did recently was helpful for one or more users, etc.). For example, as shown in the textual data 206 of FIG. 2 , a message 200 may indicate that a particular application associated with the entity is not working properly.”
[Claim 12] Gonzalaz discloses: The anomaly detection system according to claim 1, further comprising a t least one processor configured to acquire distribution content information relating to distribution content in a distribution service for distributing information relating to each of the plurality of services, [0021] (processor is configured to perform the functions based on the instructions), [Figure 3, Message ID 321] (message states capital one blanket came in the mail and the message sender loves said blanket, i.e. the system acquired information about distribution of content, i.e. information about the distribution service that sent the content and the distributed content, i.e. the blanket);
wherein at least one processor is configured to detect the anomaly of each of the plurality of services based further on the distribution content information. [0021] (processor is configured to perform the functions based on the instructions), [0026] “Social media messages that mention or otherwise indicate the entity associated with the anomaly detection system 102 may be useful in determining whether an anomaly has occurred (e.g., whether an application of the entity is not working correctly, something the entity did recently was helpful for one or more users, etc.). For example, as shown in the textual data …, a message … may indicate that a particular application associated with the entity is not working properly,” [Figure 3, Message ID 321] (message states capital one blanket came in the mail and the message sender loves said blanket, i.e. the system acquired information about distribution of content, i.e. information about the distribution service that sent the content and the distributed content, i.e. the blanket).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANGELA HATCH whose telephone number is (571)270-1393. The examiner can normally be reached 10:00-6:00.
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ANGELA HATCH
Examiner
Art Unit 3626
/ANGELA HATCH/Examiner, Art Unit 3626
/KIERSTEN V SUMMERS/Primary Examiner, Art Unit 3626
