DETAILED ACTION
This action is responsive to claims filed on 17 July 2023.
Claims 1-20 are pending for examination.
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 .
Claim Objections
Claim 5 is objected to because of the following informalities: “the uniform resource locator (URL)” in line 3 should be “the contextual uniform resource locator (URL)”. Appropriate correction is required.
Claim 19 is objected to because of the following informalities: “The system of claim 16” in line 1 should be “The system of claim 18”. Appropriate correction is required.
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 a judicial exception, abstract idea, without significantly more.
Step 1: This part of the eligibility analysis evaluates whether the claim(s) falls within any statutory
category. MPEP 2106.03:
According to the first part of the Alice analysis, in the instant case, the claims were determined
to be directed to one of the four statutory categories: an article of manufacture, a method/process (Claims 1-15), a machine/system/product (Claims 16-20), and a composition of matter. Based on the claims being determined to be within of the four categories (i.e., process, machine, manufacture, or composition of matter), (Step 1), it must be determined if the claims are directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea).
Step 2A Prong One: This part of the eligibility analysis evaluates whether the claim(s) recites a
judicial exception.
Regarding independent claims 1, 16, 20, the claims recite a judicial exception (i.e., an abstract idea enumerated in the 2019 PEG) without significantly more (Step-2A: Prong One). The applicant's claim limitations under broadest reasonable interpretation covers activities classified under mental processes - concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection Ill) and the 2019 PEG. As evaluated below:
Claims 1, 16, 20:
“programmatically analyzing content of the second portion to select a machine learning model” (mental process of evaluation)
“determining, for the user, the input to the second portion using the selected machine learning model” (mental process of judgement)
If the identified limitation(s) falls within at least one of the groupings of abstract ideas, it is
reasonable to conclude that the claim(s) recites an abstract idea in Step 2A Prong One.
Step 2A Prong Two: This part of the eligibility analysis evaluates whether the claim(s) as a whole integrates the recited judicial exception into a practical application of the exception. As evaluated below:
“wherein the second portion is configured to receive an input from a user”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions for mere data gathering or data output, see MPEP 2106.05(g).
“receiving an instruction to move a component from a first portion of a user interface to a second portion of the user interface for application on the second portion of the user interface”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception, see MPEP 2106.05(h).
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 when considered as an ordered combination and as a whole.
Step 2B: This part of the eligibility analysis evaluates whether the claim, as a whole, amounts to
significantly more than the recited exception, i.e., whether any additional element, or combination of
additional elements, adds an inventive concept to the claim. MPEP 2106.05.
First, the additional elements considered as part of the preamble and the additional elements
directed to the use of computer technology are deemed insufficient to transform the judicial exception
to a patentable invention to a patentable invention because they generally link the judicial exception to
the technology environment, see MPEP 2106.05(h).
Second, the additional elements directed to mere application of the abstract idea or mere instructions to implement an abstract idea on a computer are deemed insufficient to transform the judicial exception to a patentable invention to a patentable invention because the limitations generally apply the use of a generic computer and/or process with the judicial exception, see MPEP 2106.05(f).
Third, the claims are directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception. The courts have found these types of limitations insufficient to transform the judicial exception to a patentable invention, see MPEP 2106.05(g).
Lastly, the claims directed to data gathering activity as noted above, are deemed directed to an insignificant extra-solution activity. The courts have found these types of limitations insufficient to
qualify as "significantly more", see MPEP 2106.05(g).
Furthermore, when considering evidence in view of Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018), see USPTO Berkheimer Memorandum (April 2018). Examiner notes Berkheimer: Option 2 - A citation to one or more of the court decisions discussed in MPEP § 2106.05(d}(II} as noting the well understood, routine, conventional nature of the additional element (s) (e.g., limitations directed to mere data gathering):
The courts have recognized the following computer functions as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity, see MPEP 2106.05(d).
The additional limitations, as analyzed, failed to integrate a judicial exception into a practical application at Step 2A and provide an inventive concept in Step 2B, per the analysis above. Thus, considering the additional elements individually and in combination and the claims as a whole, the additional elements do not provide significantly more than the abstract idea. This claim is not patent eligible. Therefore, in examining elements as recited by the limitations individually and as an ordered combination, as a whole, claims 1, 16, 20 do not recite what the courts have identified as "significantly more".
Furthermore, regarding dependent claims 2-15, which depend from claim 1, claims 17-19, which depend from claim 16, the claims are directed to a judicial exception (i.e., an abstract idea enumerated in the 2019 PEG, a law of nature, or a natural phenomenon) without significantly more as highlighted below in the claim limitations by evaluating the claim limitations under the Step2A and 2B:
Claims 2, 17:
Incorporates the rejections of claims 1, 16, respectively.
“wherein the instruction to move a component from a first portion of a user interface to a second portion of the user interface includes dragging the component from the first portion and dropping the component to the second portion to cause the component to be applied to the second portion of the user interface”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception, see MPEP 2106.05(h).
Limitations directed to mere instructions indicating a field of use or technological environment in which to apply a judicial exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claims 3, 18:
Incorporates the rejections of claims 1, 16, respectively.
“determining at least one host capability of an application associated with the user interface” (mental process of judgement)
The recitation is directed to mere instructions to implement an abstract idea on a computer, or
merely uses a computer as a tool to perform an abstract idea and are considered to adding the words "apply it" (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to mere instructions to implement an abstract idea on a computer/using computer as a tool cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claims 4, 19:
Incorporates the rejections of claims 3, 18, respectively.
“wherein the at least one host capability of the application associated with the user interface is determined based on at least one of: a host name or a contextual uniform resource locator (URL)”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception, see MPEP 2106.05(h).
Limitations directed to mere instructions indicating a field of use or technological environment in which to apply a judicial exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 5:
Incorporates the rejection of claim 4.
“parsing the uniform resource locator (URL) to extract at least one keyword” (mental process of evaluation)
“determining a function of a page associated with the application based at least on a lookup of the at least one keyword in a lookup table” (mental process of judgement)
The recitation is directed to mere instructions to implement an abstract idea on a computer, or
merely uses a computer as a tool to perform an abstract idea and are considered to adding the words "apply it" (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to mere instructions to implement an abstract idea on a computer/using computer as a tool cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 6:
Incorporates the rejection of claim 1.
“determining at least one of a configuration or a property of an application associated with the user interface” (mental process of judgement)
The recitation is directed to mere instructions to implement an abstract idea on a computer, or
merely uses a computer as a tool to perform an abstract idea and are considered to adding the words "apply it" (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to mere instructions to implement an abstract idea on a computer/using computer as a tool cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 7:
Incorporates the rejection of claim 6.
“wherein the configuration or the property of the application associated with the user interface includes at least one of: metadata of a page associated with the application, a widget, or a Document Object Model (DOM) element”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception, see MPEP 2106.05(h).
Limitations directed to mere instructions indicating a field of use or technological environment in which to apply a judicial exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 8:
Incorporates the rejection of claim 6.
“wherein a page type associated with the application is determined based at least on the configuration or the property of the application associated with the user interface” (mental process of judgement)
The recitation is directed to mere instructions to implement an abstract idea on a computer, or
merely uses a computer as a tool to perform an abstract idea and are considered to adding the words "apply it" (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to mere instructions to implement an abstract idea on a computer/using computer as a tool cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 9:
Incorporates the rejection of claim 1.
“determining a page of an application associated with the second portion and selecting the machine learning model based at least on the io determined page” (mental process of judgement)
The recitation is directed to mere instructions to implement an abstract idea on a computer, or
merely uses a computer as a tool to perform an abstract idea and are considered to adding the words "apply it" (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to mere instructions to implement an abstract idea on a computer/using computer as a tool cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 10:
Incorporates the rejection of claim 9.
“wherein information associated with the determined page is used to train the machine learning model”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception, see MPEP 2106.05(h).
Limitations directed to mere instructions indicating a field of use or technological environment in which to apply a judicial exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 11:
Incorporates the rejection of claim 1.
“determining an action to perform with respect to the is second portion on behalf of the user” (mental process of judgement)
The recitation is directed to mere instructions to implement an abstract idea on a computer, or
merely uses a computer as a tool to perform an abstract idea and are considered to adding the words "apply it" (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to mere instructions to implement an abstract idea on a computer/using computer as a tool cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 12:
Incorporates the rejection of claim 1.
“using the selected machine learning model to determine permitted actions to take with respect to the second portion” (mental process of judgement)
The recitation is directed to mere instructions to implement an abstract idea on a computer, or
merely uses a computer as a tool to perform an abstract idea and are considered to adding the words "apply it" (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to mere instructions to implement an abstract idea on a computer/using computer as a tool cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 13:
Incorporates the rejection of claim 12.
“further comprising taking at least one action from among the determined permitted actions to take with respect to the second portion”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception, see MPEP 2106.05(h).
Limitations directed to mere instructions indicating a field of use or technological environment in which to apply a judicial exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 14:
Incorporates the rejection of claim 13.
“wherein taking the at least one action includes populating data in the second portion using a key-value pair for at least one link in the second portion”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception, see MPEP 2106.05(h).
Limitations directed to mere instructions indicating a field of use or technological environment in which to apply a judicial exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Claim 15:
Incorporates the rejection of claim 13.
“determining at least one applicable rule for the second portion” (mental process of judgement)
The recitation is directed to mere instructions to implement an abstract idea on a computer, or
merely uses a computer as a tool to perform an abstract idea and are considered to adding the words "apply it" (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
“validating data in the second portion based on at least one rule”
These recitations are deemed insufficient to transform the judicial exception to a patentable invention because the recitation is directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception, see MPEP 2106.05(h).
Limitations directed to mere instructions to implement an abstract idea on a computer/using computer as a tool or directed to instructions merely indicating a field of use or technological environment in which to apply a judicial exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
The dependent claims as analyzed above, do not recite limitations that integrated the judicial exception into a practical application. In addition, the claim limitations do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step-2B). Therefore, the claims do not recite any limitations, when considered individually or as a whole, that recite what have the courts have identified as "significantly more", see MPEP 2106.05; and therefore, as a whole the claims are not patent eligible. As shown above, the dependent claims do not provide any additional elements that when considered individually or as an ordered combination, amount to significantly more than the abstract idea identified. Therefore, as a whole, the dependent claims do not recite what have the courts have identified as "significantly more" than the recited judicial exception. Therefore, claims 2-15, 17-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception and does not recite, when claim elements are examined individually and as a whole, elements that the courts have identified as "significantly more" than the recited judicial exception.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-2, 6-7, 9-11,16-17, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Silverstein et al. (U.S. Pre-Grant Publication No. 20220405064, hereinafter ‘Silverstein'), in view of Reardon et al. (U.S. Pre-Grant Publication No. 20240111408, hereinafter 'Reardon').
Regarding claim 1 and analogous claims 16, 20, Silverstein teaches A method, comprising ([0068] The present invention may be embodied as a system, a method, and/or a computer program product. The computer program product may include a computer-readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.):
programmatically analyzing content of the second portion to select a machine learning model ([0021] Embodiments of the present disclosure utilize trained machine learning to identify elements on a user interface page. The machine learning models used in the present disclosure may use object recognition functionality. The machine learning models extract subcomponents, aspects, and attributes of identified elements using object recognition.; [0047] In operation 530, the model component 150 generates an artifact schema. The artifact schema may be actionable, used as input for to select a machine learning model machine learning models and generation of RPA bot generated content. The artifact schema may include programmatically analyzing content of the second portion artifacts that are able to be captured based on visual processing by feeding a desired webpage, uniform resource locator (URL), or user interface to components of the present disclosure.); and
determining, for the user, the input to the second portion using the selected machine learning model ([0021] Embodiments of the present disclosure utilize trained machine learning to identify elements on a user interface page. The machine learning models used in the present disclosure may use object recognition functionality. The machine learning models extract subcomponents, aspects, and attributes of identified elements using object recognition.; [0047] In operation 530, the model component 150 generates an artifact schema. The artifact schema may be actionable, used as input for using the selected machine learning model machine learning models and generation of RPA bot generated content. The artifact schema may include artifacts that are able to be captured based on to the second portion visual processing by feeding a desired webpage, uniform resource locator (URL), or determining, for the user, the input user interface to components of the present disclosure.).
Silverstein fails to teach receiving an instruction to move a component from a first portion of a user interface to a second portion of the user interface for application on the second portion of the user interface, wherein the second portion is configured to receive an input from a user;
Reardon teaches receiving an instruction to move a component from a first portion of a user interface to a second portion of the user interface for application on the second portion of the user interface, wherein the second portion is configured to receive an input from a user ([0059] In addition, the webpage data 218 includes a DND library customized for the given webpage. In certain embodiments, the product platform 210 retrieves the core of the DND library and one or more adapters from the DND database 230 depending on the content of the webpage and the type of animation effects required to illustrate the DND operation.; [0067] In some embodiments, the native DND API 224 monitors user interaction with a displayed webpage and defines a number of events related to DND operations, which fire when certain user interactions are detected. Events fired by the DND API 224 are referred to as API events herein. For example, during a DND operation, the native API 224 may fire a “dragstart” event when it detects that a user has receiving an instruction to move a component from a first portion of a user interface selected a “draggable” item and has commenced wherein the second portion is configured to receive an input from a user moving their input control across the user interface. Similarly, it may fire a “dragend” event when it detects that the user has stopped the dragging action and released the selected draggable item at a location other than a valid drop location on the user interface. After “dragstart”, the native API 224 may continue to fire “drag” events until it detects that the operation has ended or the draggable item is over a potential drop target. A “drageneter” event may be fired when the API detects that during a dragging operation a cursor has entered a potential drop target, and a “dragleave” event may be fired when the API detects that the cursor has left the potential drop target. Further still, the API may fire a to a second portion of the user interface for application on the second portion of the user interface “drop” event when the selected draggable item is dropped on a valid drop target.);
Silverstein and Reardon are considered to be analogous to the claimed invention because they are in the same field of application processing via graphical user interfaces. In view of the teachings of Silverstein, it would have been obvious for a person of ordinary skill in the art to apply the teachings of Reardon to Silverstein before the effective filing date of the claimed invention in order to provide a new and improved DND library, reducing load times and also reducing browser-processing requirements when performing DND operations (cf. Reardon, [0038] To address one or more of these issues, aspects of the present disclosure provide a new and improved DND library. In particular, aspects of the present disclosure provide a DND library that is only a few kilobytes in size. Further, the library is not only smaller in size than previously known libraries, but also much simpler than previously known libraries. Because of its smaller size and simplicity, the DND library presently disclosed significantly reduces load times and also reduces browser-processing requirements when performing DND operations.).
Regarding claim 2 and analogous claim 17, Silverstein, as modified by Reardon, teaches The method of claim 1 and The system of claim 16, respectively.
Reardon teaches wherein the instruction to move a component from a first portion of a user interface to a second portion of the user interface includes dragging the component from the first portion and dropping the component to the second portion to cause the component to be applied to the second portion of the user interface ([0067] In some embodiments, the native DND API 224 monitors user interaction with a displayed webpage and defines a number of events related to DND operations, which fire when certain user interactions are detected. Events fired by the DND API 224 are referred to as API events herein. For example, during a DND operation, the native API 224 may fire a instruction to move a component from a first portion of a user interface to a second portion of the user interface includes dragging the component from the first portion “dragstart” event when it detects that a user has selected a “draggable” item and has commenced moving their input control across the user interface. Similarly, it may fire a “dragend” event when it detects that the user has stopped the dragging action and released the selected draggable item at a location other than a valid drop location on the user interface. After “dragstart”, the native API 224 may continue to fire “drag” events until it detects that the operation has ended or the draggable item is over a potential drop target. A “drageneter” event may be fired when the API detects that during a dragging operation a cursor has entered a potential drop target, and a “dragleave” event may be fired when the API detects that the cursor has left the potential drop target. Further still, the API may fire a and dropping the component to the second portion to cause the component to be applied to the second portion of the user interface “drop” event when the selected draggable item is dropped on a valid drop target.).
Silverstein and Reardon are combinable for the same rationale as set forth above with respect to claim 1.
Regarding claim 6, Silverstein, as modified by Reardon, teaches The method of claim 1.
Silverstein teaches wherein programmatically analyzing content of the second portion to select a machine learning model includes determining at least one of a configuration or a property of an application associated with the user interface ([0045] The model component 150 may generate a user interface model for the thematic information or a plurality of user interface models. In some instances, the model component 150 generates the set of user interface models so that each model or a subset of models is generated for distinct portions or aspects of the thematic information of the interface, web page, website, or other interface environment.; [0032] In some embodiments, the operation 220 is performed by passing a full page or view of the interface environment to a machine learning model generated for a larger thematic environment in which the interface environment is being developed. The thematic component 110, using the machine learning model, differentiates and visually identifies each and every present element within the screen. Each element is tagged with metadata components. The determining at least one of a configuration or a property of an application associated with the user interface metadata components may include field names, coordinates of an input area (e.g., X,Y coordinates within the interface environment), element types, associated or proximate elements, and element hierarchies.).
Silverstein and Reardon are combinable for the same rationale as set forth above with respect to claim 1.
Regarding claim 7, Silverstein, as modified by Reardon, teaches The method of claim 6.
Silverstein teaches wherein the configuration or the property of the application associated with the user interface includes at least one of: metadata of a page associated with the application, a widget, or a Document Object Model (DOM) element ([0045] The model component 150 may generate a user interface model for the thematic information or a plurality of user interface models. In some instances, the model component 150 generates the set of user interface models so that each model or a subset of models is generated for distinct portions or aspects of the thematic information of the interface, web page, website, or other interface environment.; [0032] In some embodiments, the operation 220 is performed by passing a full page or view of the interface environment to a machine learning model generated for a larger thematic environment in which the interface environment is being developed. The thematic component 110, using the machine learning model, differentiates and visually identifies each and every present element within the screen. Each element is tagged with metadata components. The metadata of a page associated with the application metadata components may include field names, coordinates of an input area (e.g., X,Y coordinates within the interface environment), element types, associated or proximate elements, and element hierarchies.; [0039] The components may identify the thematic elements of Product A and train a model based on the thematic elements and user interface elements within Product A. The components may automatically parse HTML and or a Document Object Model (DOM) element DOM object model elements to identify and understand elements of Product A.).
Silverstein and Reardon are combinable for the same rationale as set forth above with respect to claim 1.
Regarding claim 9, Silverstein, as modified by Reardon, teaches The method of claim 1.
Silverstein teaches wherein programmatically analyzing content of the second portion to select a machine learning model includes determining a page of an application associated with the second portion and selecting the machine learning model based at least on the determined page ([0032] In some embodiments, the operation 220 is performed by determining a page of an application associated with the second portion and selecting the machine learning model based at least on the determined page passing a full page or view of the interface environment to a machine learning model generated for a larger thematic environment in which the interface environment is being developed. The thematic component 110, using the machine learning model, differentiates and visually identifies each and every present element within the screen.).
Silverstein and Reardon are combinable for the same rationale as set forth above with respect to claim 1.
Regarding claim 10, Silverstein, as modified by Reardon, teaches The method of claim 9.
Silverstein teaches wherein information associated with the determined page is used to train the machine learning model ([0041] In operation 510, the thematic component 110 performs object recognition on a set of themed interface attributes within a set of themed graphical user interfaces. The thematic component 110 may perform object recognition of enterprise theming and consistent UI elements present within an application, an application suite, a web page, a web site, or any other graphical content.; [0039] For example, as described by the method 200, a developer may be building out automation for a company. The company may use a theme throughout their enterprise on process and workflow tools of product A. Product A elements may use a standard theme. At least a portion of product A may be exposed to the components of the automated programming system 102. The components may identify the thematic elements of Product A and wherein information associated with the determined page is used to train the machine learning model train a model based on the thematic elements and user interface elements within Product A.).
Silverstein and Reardon are combinable for the same rationale as set forth above with respect to claim 1.
Regarding claim 11, Silverstein, as modified by Reardon, teaches The method of claim 1.
Silverstein teaches wherein determining the input to the second portion using the selected machine learning model includes determining an action to perform with respect to the second portion on behalf of the user ([0033] At operation 230, the interaction component 120 generates a set of automated interactions. In some embodiments, the set of determining an action to perform with respect to the second portion on behalf of the user automated interactions are generated based on the interface environment, the set of user interface elements, the set of element attributes, and the user interface model.).
Silverstein and Reardon are combinable for the same rationale as set forth above with respect to claim 1.
Claims 3-5, 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Silverstein, in view of Reardon, and further in view of Guruswamy et al. (U.S. Patent No. 8799714, hereinafter 'Guruswamy').
Regarding claim 3 and analogous claim 18, Silverstein, as modified by Reardon, teaches The method of claim 1 and The system of claim 16, respectively.
Silverstein, as modified by Reardon, fails to teach wherein programmatically analyzing content of the second portion to select a machine learning model includes determining at least one host capability of an application associated with the user interface.
Guruswamy teaches wherein programmatically analyzing content of the second
portion to select a machine learning model includes determining at least one host capability of an application associated with the user interface ([Col. 8, Lines 6-14] In some example embodiments, the converter tool 110 may generate an additional transport to represent communication between the application host 106 and a Domain Name Service (DNS) host 116. For example, determining at least one host capability of an application associated with the user interface URL's included in request messages generated by the application host 106 may be provided to a DNS host 116, which may return the symbolic (e.g., numeric) network address of the destination host identified by the URL.; [Col. 8, Lines 19-34] At 504, the converter tool 110 may identify hosts from the captured transaction. The identified hosts may also be stored at a table of hosts, which can be a part of the processed message scenario 210. The application host 106 may be considered a first host. In some example embodiments, the DNS host 116 is represented as a second identified host. For example, the converter tool 110 may be configured to emit DNS queries to resolve the names of other hosts participating in the transaction. Additional hosts may be determined by examining the URL's of the messages in the transaction. Upon encountering a new host referenced in a message URL, the converter tool 110 may emit a DNS query to identify the name of the encountered host. Upon determining the host name, the converter tool 110 may perform a map look-up at the table of hosts to determine if the encountered host is in the table.).
Silverstein, Reardon, and Guruswamy are considered to be analogous to the claimed invention because they are in the same field of application processing via graphical user interfaces. In view of the teachings of Silverstein and Reardon, it would have been obvious for a person of ordinary skill in the art to apply the teachings of Guruswamy to Silverstein before the effective filing date of the claimed invention in order to determine hosts taking part in the transaction as well as the transports used for the transaction (cf. Guruswamy, [Col. 2, Line 60-Col. 3, Line 5] Captured messages may be processed and converted to one or more test scenarios, for example, by a converter tool executed by a computer system. Processing transaction messages may involve extracting various information from the messages as well as making various modifications to the messages. For example, the converter tool may determine hosts taking part in the transaction as well as the transports used for the transaction. In some example embodiments, the converter tool also associates corresponding request and response messages with one another. Additionally, in some example embodiments, the converter tool filters transaction messages to remove messages that do not affect the end result of the transaction.).
Regarding claim 4 and analogous claim 19, Silverstein, as modified by Reardon and Guruswamy, teaches The method of claim 3 and The system of claim 18, respectively.
Guruswamy teaches wherein the at least one host capability of the application associated with the user interface is determined based on at least one of: a host name or a contextual uniform resource locator (URL) ([Col. 8, Lines 6-14] In some example embodiments, the converter tool 110 may generate an additional transport to represent communication between the application host 106 and a Domain Name Service (DNS) host 116. For example, URL's included in request messages generated by the application host 106 may be provided to a DNS host 116, which may return the host capability of the application associated with the user interface is determined based on at least one of: a host name symbolic (e.g., numeric) network address of the destination host or a contextual uniform resource locator (URL) identified by the URL.; [Col. 8, Lines 19-34] At 504, the converter tool 110 may identify hosts from the captured transaction. The identified hosts may also be stored at a table of hosts, which can be a part of the processed message scenario 210. The application host 106 may be considered a first host. In some example embodiments, the DNS host 116 is represented as a second identified host. For example, the converter tool 110 may be configured to emit DNS queries to resolve the names of other hosts participating in the transaction. Additional hosts may be determined by examining the URL's of the messages in the transaction. Upon encountering a new host referenced in a message URL, the converter tool 110 may emit a DNS query to identify the name of the encountered host. Upon determining the host name, the converter tool 110 may perform a map look-up at the table of hosts to determine if the encountered host is in the table.).
Silverstein, Reardon, and Guruswamy are combinable for the same rationale as set forth above with respect to claim 3.
Regarding claim 5, Silverstein, as modified by Reardon and Guruswamy, teaches The method of claim 4.
Guruswamy teaches wherein determining the at least one host capability of the application associated with the user interface includes: parsing the uniform resource locator (URL) to extract at least one keyword; and determining a function of a page associated with the application based at least on a lookup of the at least one keyword in a lookup table ([Col. 8, Lines 6-14] In some example embodiments, the converter tool 110 may generate an additional transport to represent communication between the application host 106 and a Domain Name Service (DNS) host 116. For example, URL's included in request messages generated by the application host 106 may be provided to a DNS host 116, which may return the symbolic (e.g., numeric) network address of the destination parsing the uniform resource locator (URL) to extract at least one keyword host identified by the URL.; [Col. 8, Lines 19-38] At 504, the converter tool 110 may identify hosts from the captured transaction. The identified hosts may also be stored at a table of hosts, which can be a part of the processed message scenario 210. The application host 106 may be considered a first host. In some example embodiments, the DNS host 116 is represented as a second identified host. For example, the converter tool 110 may be configured to emit DNS queries to resolve the names of other hosts participating in the transaction. Additional hosts may be determined by examining the URL's of the messages in the transaction. Upon encountering a new host referenced in a message URL, the converter tool 110 may emit a DNS query to identify the name of the encountered host. Upon determining the host name, the converter tool 110 may based at least on a lookup of the at least one keyword in a lookup table perform a map look-up at the table of hosts to determine if the encountered host is in the table. If the encountered host is not included in the table, the converter 100 may add it. determining a function of a page associated with the application Each transaction host may be identified using any suitable descriptors. In some example embodiments, some or all of the hosts may be identified by a name and a protocol family (e.g., IPv4, IPv6, etc.).).
Silverstein, Reardon, and Guruswamy are combinable for the same rationale as set forth above with respect to claim 3.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Silverstein, in view of Reardon, and further in view of Shenfield et al. (U.S. Pre-Grant Publication No. 20060200748, hereinafter 'Shenfield').
Regarding claim 8, Silverstein, as modified by Reardon, teaches The method of claim 6.
Silverstein, as modified by Reardon, fails to teach wherein a page type associated with the application is determined based at least on the configuration or the property of the application associated with the user interface.
Shenfield teaches wherein a page type associated with the application is determined based at least on the configuration or the property of the application associated with the user interface ([0057] The wherein a page type associated with the application is determined based at least on the configuration or the property of the application associated with the user interface page analyzer module 110 assembles the page metadata from the input application 107 from page analysis and/or from source code. For the source code example, the module 110 parses each presentation page/screen (i.e. display output to a user interface of a client computer) from the source code and then collects the metadata for each presentation page. The module 110 includes the characteristics of navigation and other user event links, presentation styles/format, page type and data dependencies for each set of page metadata corresponding to the respective pages of the input application 107. For the page analysis example, the module 110 validates the presented web page displayed on the user interface 502 (see FIG. 5) of the user computer 14, analyzes the page type, retrieves the navigation and any other user event links, determines the page styles and formats, and notes the data dependencies. The module 110 then builds the representative metadata for each presentation page of the input application 107. The page metadata for each presentation page of the input application is then made available to the conversion module 113. It is recognised that the module 110 could also be coupled to a comparison module 600 (see FIG. 6) for determining the scale of the pages of the application 107 as compared to the best suited scale of the presentation content (of the pages) for the UI 202 of the device.).
Silverstein, Reardon, and Shenfield are considered to be analogous to the claimed invention because they are in the same field of application processing via graphical user interfaces. In view of the teachings of Silverstein and Reardon, it would have been obvious for a person of ordinary skill in the art to apply the teachings of Shenfield to Silverstein before the effective filing date of the claimed invention in order to provide a conversion capability to transform page-based applications to component based applications including workflow to obviate or mitigate at least some of the presented disadvantages (cf. Shenfield, [0003] There is a need for application programs, other than page-based applications, that can be run on client devices having a wide variety of runtime environments, as well as having a reduced consumption of device resources.; [0004] The systems and methods disclosed herein provide a conversion capability to transform page-based applications to component based applications including workflow to obviate or mitigate at least some of the above presented disadvantages.).
Claims 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Silverstein, in view of Reardon, and further in view of Singh et al. (U.S. Pre-Grant Publication No. 20240364586, hereinafter 'Singh').
Regarding claim 12, Silverstein, as modified by Reardon, teaches The method of claim 1.
Silverstein, as modified by Reardon, fails to teach wherein determining the input to the second portion using the selected machine learning model includes using the selected machine learning model to determine permitted actions to take with respect to the second portion.
Singh teaches wherein determining the input to the second portion using the selected machine learning model includes using the selected machine learning model to determine permitted actions to take with respect to the second portion ([0112] In some embodiments, the using the selected machine learning model to determine permitted actions to take with respect to the second portion machine learning model trained as described in connection with FIG. 7 may be utilized to identify a confidence value and/or one or more remedial action recommendations based at least in part on the data obtained and/or signals asserted/recorded by the monitoring manager 404. As a non-limiting example, the monitoring manager 404 may obtain data from any suitable source (e.g., BMC 604, Agent 424, or any suitable combination of the above). The monitoring manager 404 may analyze the data and assert/record any suitable signal indicating an occurrence of a destabilization event (e.g., console lockup, console panic, power panic, SEL panic, and/or the like). The data obtained by the monitoring manager 404 and/or the signals asserted/recorded by the monitoring manager 404 may be provided (e.g., by the remedial action engine 601) to the previously trained machine learning model. The machine learning model may take such data as input and output a confidence value indicating the existence of a destabilization event. In some embodiments, the machine learning model may additionally, or alternatively, identify one or more remedial actions. In some embodiments, destabilization events that are associated with a confidence score generated by the machine learning model that exceed a predefined threshold (e.g., 75% confidence value) may be presented to the user. For example, identified destabilization events that are 75% likely to be occurring based at least in part on the output provided by the machine learning model and/or the remedial actions corresponding to those events may be presented to the user (e.g., via client device(s) 106) via any suitable user interface. The user may select and/or permitting, selecting, and/or rejecting the remedial actions using said user interface. If user input is received permits/selects one or more remedial actions, the remedial action engine 601 may be configured to receive this input and execute operations for performing the permitted/selected remedial action(s).).
Silverstein, Reardon, and Singh are considered to be analogous to the claimed invention because they are in the same field of application processing via graphical user interfaces. In view of the teachings of Silverstein and Reardon, it would have been obvious for a person of ordinary skill in the art to apply the teachings of Singh to Silverstein before the effective filing date of the claimed invention in order for reduced and/or detected and recovery operations be automatically performed to resolve detected failures with employment of a machine-learning model (cf. Singh, [0031] The monitoring manager may be configured to employ a machine-learning model that is trained utilizing supervised learning and a training data set for which such operational data is mapped to known failures. At run-time, current operational data may be provided to the model as input to determine a likelihood that a failure is occurring and/or likely to occur. The monitoring manager can execute a variety of operations to perform remedial actions to recover from the detected failures. Using the disclosed techniques, the risk of failures occurring between these converged network adaptors and the host OSs may be reduced and/or detected and recovery operations may be automatically performed to resolve such failures.).
Regarding claim 13, Silverstein, as modified by Reardon and Singh, teaches The method of claim 12.
Singh teaches further comprising taking at least one action from among the determined permitted actions to take with respect to the second portion ([0112] In some embodiments, the machine learning model trained as described in connection with FIG. 7 may be utilized to identify a confidence value and/or one or more remedial action recommendations based at least in part on the data obtained and/or signals asserted/recorded by the monitoring manager 404. As a non-limiting example, the monitoring manager 404 may obtain data from any suitable source (e.g., BMC 604, Agent 424, or any suitable combination of the above). The monitoring manager 404 may analyze the data and assert/record any suitable signal indicating an occurrence of a destabilization event (e.g., console lockup, console panic, power panic, SEL panic, and/or the like). The data obtained by the monitoring manager 404 and/or the signals asserted/recorded by the monitoring manager 404 may be provided (e.g., by the remedial action engine 601) to the previously trained machine learning model. The machine learning model may take such data as input and output a confidence value indicating the existence of a destabilization event. In some embodiments, the machine learning model may additionally, or alternatively, identify one or more remedial actions. In some embodiments, destabilization events that are associated with a confidence score generated by the machine learning model that exceed a predefined threshold (e.g., 75% confidence value) may be presented to the user. For example, identified destabilization events that are 75% likely to be occurring based at least in part on the output provided by the machine learning model and/or the remedial actions corresponding to those events may be presented to the user (e.g., via client device(s) 106) via any suitable user interface. The user may select and/or permitting, selecting, and/or rejecting the remedial actions using said user interface. If user input is received permits/selects one or more remedial actions, the taking at least one action from among the determined permitted actions to take with respect to the second portion remedial action engine 601 may be configured to receive this input and execute operations for performing the permitted/selected remedial action(s).).
Silverstein, Reardon, and Singh are combinable for the same rationale as set forth above with respect to claim 12.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Silverstein, in view of Reardon, Singh, and further in view of Parees et al. (U.S. Pre-Grant Publication No. 20090083337, hereinafter 'Parees').
Regarding claim 14, Silverstein, as modified by Reardon and Singh, teaches The method of claim 13.
Silverstein, as modified by Reardon and Singh, fails to teach wherein taking the at least one action includes populating data in the second portion using a key-value pair for at least one link in the second portion.
Parees teaches wherein taking the at least one action includes populating data in the second portion using a key-value pair for at least one link in the second portion ([0034] Referring to FIG. 3, in conjunction with FIGS. 1-2, in step 301, external data source 104 (e.g., online order application) modifies or creates a new row in source table 102. For example, external data source 104 may populate a row in source table 102 to include the product purchased by a buyer, the purchase price, the buyer's address, the buyer's credit card, etc. The row populated with data by external data source 104 may be associated with a process identification referred to herein as a "primary key value." That is, each row in source table 102 may be associated with a unique primary key value. For example, row #1 in source table 102 may be associated with primary key #1.).
Silverstein, Reardon, Singh, and Parees are considered to be analogous to the claimed invention because they are in the same field of application processing via graphical user interfaces. In view of the teachings of Silverstein, Reardon, and Singh, it would have been obvious for a person of ordinary skill in the art to apply the teachings of Parees to Silverstein before the effective filing date of the claimed invention in order to synchronize the relational source and target tables in an efficient manner while minimizing the contention at the source table (cf. Parees, [0003] The present invention relates to relational databases, and more particularly to performing synchronization between the relational source and target tables in an efficient manner using an application that is platform agnostic while minimizing the contention at the source table.; [0021] The application can then perform a subsequent read operation on the source table during the next data copy cycle to obtain the updated data as discussed above. In this manner, a platform agnostic application may be able to synchronize the relational source and target tables in an efficient manner while minimizing the contention at the source table.).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Silverstein, in view of Reardon, Singh, and further in view of Gogineni et al. (U.S. Pre-Grant Publication No. 20190179934, hereinafter 'Gogineni').
Regarding claim 15, Silverstein, as modified by Reardon and Singh, teaches The method of claim 13.
Silverstein, as modified by Reardon and Singh, fails to teach wherein taking the at least one action includes validating data including by: determining at least one applicable rule for the second portion; and validating data in the second portion based on at least one rule.
Gogineni teaches wherein taking the at least one action includes validating data including by: determining at least one applicable rule for the second portion; and validating data in the second portion based on at least one rule ([0040] In some example embodiments, the first client 120A and/or the second client 120B may send, to the structured data validation engine 110, one or more electronic documents including structured data for validation. The structured data may be in the form of, for example, XML documents, JSON documents, and/or the like. In response to receiving the one or more electronic documents, the structured data validation engine 110 may determining at least one applicable rule for the second portion identify an applicable validation rule set and retrieve, by at least querying the database 115, one or more validation rules included in the applicable validation rule set. The structured data validation engine 110 may further validating data in the second portion based on at least one rule validate the structured data included in the electronic documents by at least applying the validation rules retrieved from the database 115. To further illustrate, FIG. 3C depicts a user interface 370 for validating structured data, in accordance with some example embodiments. In some example embodiments, the user interface 340 may be displayed by the first browser 125A at the first client 120A and/or the second browser 125B at the second client 120B.).
Silverstein, Reardon, Singh, and Gogineni are considered to be analogous to the claimed invention because they are in the same field of application processing via graphical user interfaces. In view of the teachings of Silverstein, Reardon, and Singh, it would have been obvious for a person of ordinary skill in the art to apply the teachings of Gogineni to Silverstein before the effective filing date of the claimed invention in order to validate structured data from a client (cf. Gogineni, [0021] In some example embodiments, the validation of structured data may be offloaded to be performed by a cloud based validation engine. The cloud based validation engine may be a multitenant application capable of validating structured data originating from multiple clients. Each client may create one or more custom validation rules, which may be stored at a database coupled with the cloud based validation engine. To validate structured data from a client, the cloud based validation engine may dynamically identify, based on the structured data, a set of applicable validation rules that includes custom validation rules and/or default validation rules provided by the cloud based validation engine. The cloud based validation engine may query the database to retrieve validation rules included in the set of application validation rules. The cloud based validation engine may further apply the set of applicable validation rules in order to validate the structured data from the client.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wooldridge et al. (U.S. Patent No. 10581991) teaches analyzing tracking requests received by an online system from client devices rendering web pages received from a website, and in particular to determining accuracy of the information provided by client devices via tracking requests to an online system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAGGIE MAIDO whose telephone number is (703) 756-1953. The examiner can normally be reached M-Th: 6am - 4pm.
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/MM/Examiner, Art Unit 2129
/MICHAEL J HUNTLEY/Supervisory Patent Examiner, Art Unit 2129