DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/1/26 has been entered.
Notice to Applicant
The following is a Non-Final Office action. In response to Examiner’s Final Rejection of 12/3/25, Applicant, on 3/1/26, amended claims. Claims 1-7 are pending in this application and have been rejected below.
Response to Amendment
Applicant’s amendments are acknowledged.
Previous 112 rejections are withdrawn in light of the amendments; however, new 112 rejections are necessitated by the amendments.
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 3-5 are 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.
Claim 3 recites the limitation "to further set a reference value of an operation to be visualized". There is insufficient antecedent basis for this limitation in the claim as claim 1 now recites “a reference value” and “having one or more nodes that exceeds the reference value is visualized…” It is unclear if the same reference value is referred to, or a different one. For purposes of applying prior at only, it appears portions of claim 3 are duplicative, referring to the same reference value, and can be removed.
Claim 4 recites the limitation " further generate an operation sequence in units of windows arrayed in a time series order for each case and aligns the operation sequence in units of windows… and specify windows that appear with a reference value or more at the same position in the operation sequence in units of windows of each case as windows of the main flow… arrange nodes corresponding to the windows of the main flow in a time series order on one axis". There is insufficient antecedent basis for the bolded limitations in the claim 4, as claim 1 now recites “generate an operation sequence in units of operations arrayed in a time series order for each case on the basis of the operation log and align the operation sequence in units of operations; align the operation sequence based on a granularity of windows…specify operation types that appears with a reference value… visualize nodes corresponding to the operation types of the main flow in a time series order on one axis” It is unclear if the same [a) operation sequence, b) windows, c) time series order, d) aligns, and e) reference value, and f) one axis] are referred to, or different ones. For purposes of applying prior at only, it appears portions of claim 4 are duplicative, referring to the same limitations in claim 1, and can be removed. It may be that only the very last phrase of claim 4 (“superimpose…”) differs from claim 1?
Claim 5 depends from claim 4 and is rejected for the same reasons.
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 1-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without reciting significantly more.
Step One - First, pursuant to step 1 in MPEP 2106.03, the claim 1 is directed to an apparatus which is a statutory category.
Step 2A, Prong One - MPEP 2106.04 - The claim 1 recites–
A visualization display … comprising:
visualization display … configured to:
acquire an operation log;
generate an operation sequence in units of operations arrayed in a time series order for each case on the basis of the operation log and align the operation sequence in units of operations;
align the operation sequence based on a granularity of windows, wherein a set of the operation sequence is processed at the granularity of screens (See e.g. Applicant’s [0067] as published “window information related to a user’s operation, a GUI component name.”; 0157] as published “FIG. 33. The visualization unit 15c uses the alignment result (the result of alignment at the granularity of windows) to extract the position IDs (windows) that appear with a threshold or more for all the cases and the window IDs associated with the position IDs (windows), and highlights and visualizes them by lining up the window IDs on one axis “); and
specify operation types that appear with a reference value or more at the same position in the operation sequence in units of operations of each case as operation types of a main flow on the basis of the aligned operation sequence in units of operations, in which the main flow is identified by setting an operation sequence as equal to or exceeding a reference value and arrange and visualize nodes corresponding to the operation types of the main flow in a time series order on one axis, wherein
all nodes representing operation types are arranged in an array and the main flow having one or more nodes that exceeds the reference value is visualized as first visualization array and one or more nodes that do not exceed the reference value is visualized as second visualization array; and
display the one or more nodes that exceeds the reference value on a display, in which the one or more nodes are displayed by respective window identification and position identification and one or more nodes that are below the reference value is displayed at different position.”
As drafted, this is, under its broadest reasonable interpretation, within the Abstract idea grouping of “certain methods of organizing human activity – managing personal behavior ore relationships or interactions between people (following rules or instructions), and Mathematical Concepts (mathematical relationships), as here we have acquiring operation log, generate a sequence arrayed in a time series order for each case, aligning the operation sequence (which in claim 2 and [0069] as published can involve mathematical relationships of generating a distance vector to align different actions into a sequence of a case based on windows or screens that a person used from the log/history, and then specify “operation types” that appear within a reference value as being on a “main flow” of the sequence and arrange visualize nodes in a time series order (Applicant’s FIG. 11 is an example, where a series of actions occurs in sequence; FIG. 12 , [0096] “other than the main flow”; FIG. 13 – showing other examples of “main flow” and another flow), where the operations being aligned in sequence include a simple sequence of operations of step 1, step 2, step 3 to form a business process (i.e. a case), different activities by a person/worker where “main flow” are those nodes greater than a reference value (e.g. [0095] as published – >80%, in eight out of 10 cases) are in the “main flow”; a second visualization for cases that do not satisfy the threshold (e.g. [0112] as published; [0160-0161] as published – “other than the main flow” in FIG. 34)) where the nodes have “window identification” and “position identification”. The claim is directed to following mathematical rule of comparing to a threshold, to visualize a business process of operations (e.g. A-B-C-D) from a historical operation log for a “main flow” on one axis and then operations that are not satisfying a threshold are also visualized in a second visualization (e.g. A-E-C-D on a second axis, in Applicant’s example FIG. 12 or FIG. 34). The claim covers a series of rules for a person to generate a sequence of steps representing a “frequent” process from a log history of actions already performed. The business process here, as gathered from a log of historical user operations, is at the “granularity” of windows/screens used, where the method and other claims cover certain methods of organizing human activity, of using rules for what is in the business process, where the business process is aligned at the “granularity” (i.e. specificity) of windows/screens used by users in the historical log.
Step 2A, Prong Two - MPEP 2106.04 - This judicial exception is not integrated into a practical application. In particular, the claim 1 recites additional elements that are:
“A visualization display device comprising:
visualization display circuitry configured to:
...
Nodes that exceed the threshold is visualized as a first visualization array;
Nodes that do not exceed the threshold is visualized as a second visualization array;
display the one or more nodes.
Individually or in combination, MPEP 2106.05f applies –the claim involves a computer (specification [0066] as published states there is a control unit 15 which is “an electronic circuit such as a central processing unit (CPU)”), and is considered “apply it [the abstract idea] on a computer” MPEP 2106.05f; merely uses a computer as a tool to perform an abstract idea – the computer is visualizing or displaying a sequence of nodes, the nodes represent the operations of the business [see e.g. 0052 “a visualization method effective for finding a main flow to collect operations performed for business execution as a log and to visualize the operation procedure in the form of a flowchart with operations of the same type as one node and the operations connected by edges as shown in FIG. 38”; [0054] as published “operation sequences lined up in the order in which operations are executed) for each case from the operation log acquired from a terminal in a business which is performed repeatedly, specifying the type of operation sequence and the number of occurrences, and setting an operation sequence equal to or more than a threshold as a main flow (flow of operations occurring frequently) on the basis of a threshold set by a user and those that are not as exceptional flows (flows of exceptional operations).” 0172 as published); computer “visualizing/displaying”, display, is considered MPEP 2106.05h field of use).
Step 2B in MPEP 2106.05 - The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of a computing system, is treated as MPEP 2106.05(f) (Mere Instructions to Apply an Exception – “Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Alice Corp., 134 S. Ct. at 235); computer “visualizing/displaying”, display, is considered MPEP 2106.05h field of use). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Independent claim 6 is directed to a method at step 1, which is a statutory category. Claim 6 recites similar limitations as claim 1 and is rejected for the same reasons at step 2a, prong one, 2a, prong 2, and step 2b.
Independent claim 7 is directed to an article of manufacture at step 1, which is a statutory category. Claim 7 recites similar limitations as claim 1 and is rejected for the same reasons at step 2a, prong one, 2a, prong 2, and step 2b.
Claims 2 also further narrows the abstract idea, by using a mathematical relationship (distance matrix and distance vector), for aligning a sequence for the flow of operations in claim 1.
Claims 3 further narrows the abstract idea by having a visualization of the main flow on one axis and visualize nodes that meet a “reference value (threshold of operation)” (See Applicant’s [0071] as published), which is a further narrowing using a mathematical relationship and further following rules to form the representation of a business process on the axis using a graph/representation with nodes and axis. The use of the computer is MPEP 2106.05f (apply it [abstract idea] on a computer) and the displaying on the computer is field of use (MPEP 2106.05h).
Claim 4 further narrows the abstract idea by further superimposing nodes/actions at positions different from the axis (See e.g. Applicant’s FIG. 34, 38; [0053, 0161] as published giving examples of how this looks with alternative paths from actions at different positions). This is a further narrowing using a mathematical relationship and further following rules to form the representation of a business process on the axis using a graph/representation with nodes and axis, with alternative steps/actions located in a different position for a person to see. The use of the computer is MPEP 2106.05f (apply it [abstract idea] on a computer) and the displaying information/labels/text/nodes on the computer for a human reader is field of use (MPEP 2106.05h).
Claim 5 depends from claim 4. Claim 5 recites similar limitations as claim 3 and is rejected for the same reasons.
Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
For more information on 101 rejections, see MPEP 2106.
Suggestions? Examiner’s suggestions, as best understood at this time, are to 1) incorporate some additional elements if possible, for “acquire an operation log.” Instead of having a table of information from a log [as the claim currently encompasses, e.g. FIG. 2], also consider 2) executing RPA, as opposed to just having a sequence of steps which could be A-B-C, same as a person would form a business model. Examiner does not believe at this time that adding such additional elements (from portions Examiner could find) will overcome the rejection as best understood; but they still would improve the claim for purposes of 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 1 and 3-7 are rejected under 35 U.S.C. 103 as being unpatentable over Oberman (US 2022/0044168), and Tokudome (WO 2020/204144).
Concerning claim 1, Oberman discloses:
A visualization display device (Oberman – see par 44 - A number of human users such as call-center agents may use agent terminals 2 which may be for example personal computers or terminals, including one or more software programs 6 to operate and display a computer desktop system 7 (e.g. displayed as user interfaces such as a GUI). In some embodiments, software programs 6 may display windows, e.g. via desktop system 7, and accept user input (e.g. via desktop system 7) and may interface with server software 22, e.g. receiving input from and sending output to software programs 6. see par 100 - FIG. 6 depicts a set of sequences and a search sequence, according to an embodiment of the present invention. A designed workflow or automation sequence 600 being created by a business analyst may have an SSTM 602 extracted, and used to search or mine for sequences) comprising:
visualization display circuitry (Oberman – See par 105 - Embodiments of the invention may include one or more article(s) (e.g. memory 120 or storage 130) such as a computer or processor non-transitory readable medium, such as for example a memory, …encoding, including or storing instructions, e.g., computer-executable instructions, which, when executed by a processor or controller, carry out methods; see par 108 - In other instances, well-known methods, procedures, and components, modules, units and/or circuits have not been described in detail so as not to obscure the invention) configured to:
acquire an operation log (Oberman – see par 21 - low-level user action information or description data (e.g. user action items) may be for example stored and/or transmitted to for example a server or other computer. In one embodiment, data collected may be in the form of Windows Handles and their properties as provided by Windows API (e.g. Win-32). The event logs files describing these data collected desktop events collected may be stored exported using JSON files. Other low-level event or action data may be used.);
generate an operation sequence in units of operations arrayed in a time series order for each case on the basis of the operation log and align the operation sequence in units of operations (Oberman – see par 35 - FIG. 2 is an example of a sequence of actions forming a process according to embodiments of the present invention. Referring to FIG. 2, actions A, G, H and X are business process actions are performed on screen elements, such as entering text to a field. Robust actions G′ and H′ may be actions that ensure that actions, G and H respectively, may execute successfully. See par 40 - technologies exist to obtain high-level system-specific event logs as input data, such as case ID (e.g. “Process ID”), activity ID and, timestamp to identify user activity or input. A case ID may identify the process instance and an activity ID may specify the task that has been performed as part of the process; see par 53-54 – building automation workflow or automation sequence by identifying sequences (e.g. series of actions identified as business processes). See par 61 - In operation 216, a next action may be found for suggestion. For example, a set of actions from the sequence the business analyst is creating, e.g. the designed workflow or automation sequence, may be defined and sent, for example by AS 14, to automation assistant module 26, requesting suggested actions to display to the designer. The set of actions from the sequence the business analyst is creating, a segment of cut-out actions segment from the workflow, may be termed search-sequence-to-match (“SSTM”). See par 72 - In the second phase or operation, the SSTM may be used to search over the resultant candidate sequences, e.g. by aligning the SSTM and measuring a distance to each candidate sequence);
align the operation sequence based on a granularity of windows, wherein a set of the operation sequence is processed at the granularity of screens (See e.g. Applicant’s [0067] as published “window information related to a user’s operation, a GUI component name.”; [0157] as published “FIG. 33. The visualization unit 15c uses the alignment result (the result of alignment at the granularity of windows) to extract the position IDs (windows) that appear with a threshold or more for all the cases and the window IDs associated with the position IDs (windows), and highlights and visualizes them by lining up the window IDs on one axis “
Oberman – see par 39 - In contrast, the low level event data recorded and used in embodiments of the present invention may not be associated with a specific process (e.g. case ID) or activity but rather may be associated only with a window which has a name and with a program or application operating the window (e.g. an internet browser). The title (e.g., the label displayed at the top) of the screen window, and the name of the program executing with which the user is interacting are data may be extracted or obtained and are different from, the specific identification of the process or program instance which in some cases may not be obtained. Event log data such as an activity ID may be data internal to a program, and may not be provided to other programs; in contrast data such as window names may be more accessible and agnostic to the various programs and applications. see par 43 - input may be a log or database of desktop actions, e.g. user input or actions to a GUI for a variety of applications (disclosing a sequence based on granularity of windows and screens) performed by one or more employees. Data describing an action may include for example action data or input type descriptions (e.g. describing whether the input is via mouse or keyboard, or what type or input such as left click, right click, cut, paste, typing text), timestamp, application context, user name, screen window information such as title or name (e.g., as computer processes in this context may be displayed as windows, each window may have a title or name which may describe the user-facing application to which the user provides input), and where possible, field context (disclosing a sequence based on granularity of windows and screens). see par 61 - The set of actions from the sequence the business analyst is creating, a segment of cut-out actions segment from the workflow, may be termed search-sequence-to-match (“SSTM”). for example, the last several (e.g. 3, 4 or 5) actions, possibly defined by a window, may be selected as the set. see par 72 - In the second phase or operation, the SSTM may be used to search over the resultant candidate sequences, e.g. by aligning the SSTM and measuring a distance to each candidate sequence. see par 93 - In operation 506 the candidate sequences found or mined in operation 504 may be filtered and an alignment score or rating determined. For example the results may be filtered by length such that only sequences that are higher or equal in length to the length of SSTM 502′ may be kept, and those shorter may be filtered out or removed.); and
specify operation types that appear with a reference value or more at the same position in the operation sequence in units of operations of each case as operation types of a main flow (Applicant’s [0003] as published - For example, in a case where a business analyst attempts to find a location to which robotic process automation (hereinafter referred to as “RPA”) can be applied from a flowchart, it is said that it is effective for the business analyst to first find a location where RPA can be applied effectively, for example, a common and repeated operation procedure (hereinafter referred to as a “main flow”) among operations for each case.
Oberman – See par 67 - The search for action sequences corresponding to the SSTM may be performed via, for example, two operations. In the first phase or operation a sequential generator pattern mining algorithm generates candidate sequences from the initial sequence pool, via a mining operation… . For example, frequent sequential patterns generators may be found or discovered (e.g. mined) using a Frequent Sequential Generator Patterns (“FSGP”) process from the pool (e.g. the listed sequences) with length equal or longer than a search-sequence-to-match length; A sequential generator pattern may be a sequential pattern SA such that there does not exists a smaller pattern SB having the same support (e.g. number of occurrences) and such that SB occurs in SA. see par 68 - A frequent sequential pattern may be a sequential pattern having a support (e.g. occurrence in a database, possibly divided by the total number of entries in the database) no less than a certain number or parameter (e.g. a minsup parameter).) on the basis of the aligned operation sequence in units of operations (Oberman - see par 73 - As part of operation 216, the list of results may be ranked or ordered, for example by factors such as: [0074] a. Alignment score (e.g. a measure of how well the returned sequence aligns with the SSTM); [0075] b. Embedded routine vector cosine distance (e.g. distance from the SSTM); see par 76 - FSGP support score), …and arrange and visualize nodes corresponding to the operation types of the main flow in a time series order … (Oberman – see par 93 - In operation 506 the candidate sequences found or mined in operation 504 may be filtered and an alignment score or rating determined. Each remaining candidate sequence (after filtering) may be aligned to SSTM 502′ and may receive an alignment score or rating that rates how well each sequence matches the sequence in SSTM 502; see par 98 - In operation 512, candidate sequences may be selected based on a composite score or rating, and from each of the selected sequences, a suggested or projected next business action may be extracted. The suggested or projected next business action may be extracted or identified as being the subsequent new action occurring in the sequence immediately after the last action matching an action from the SSTM. E.g. if the SSTM is (G,H,X) and the suggested sequence is (G,H,K,R), K is suggested. See par 0100- FIG. 6 depicts a set of sequences and a search sequence. A designed workflow or automation sequence 600 being created by a business analyst may have an SSTM 602 extracted, and used to search or mine for sequences. A pool 610 may include a recording 612 from one specific agent and routines 614 from routines collected from many agents. Each sequence 612 and 614 may include a series of actions 608. Suggested action 620 may be the next action in a sequence 614 occurring immediately after the actions which themselves match the SSTM, the sequence including action 620 being rated the highest).
Oberman discloses an example of a sequence of actions forming a process in FIG. 2 (See par 35) where the Figure shows an axis, but it is not explicitly disclosed as being part of later embodiments. Oberman discloses having a sequence of actions based on searching for best next actions to include and graphically showing the nodes/actions (608 in FIG. 6 – See par 100). However, this does not explicitly show an axis.
Tokudome discloses “on one axis”:
specify operation types that appear with a reference value or more at the same position in the operation sequence in units of operations of each case as operation types of a main flow on the basis of the aligned operation sequence in units of operations, “in which the main flow is identified by setting an operation sequence as equal to or exceeding a reference value” and arrange and visualize nodes corresponding to the operation types of the main flow in a time series order “on one axis” (Applicant’s [0157] as published “FIG. 33. The visualization unit 15c uses the alignment result (the result of alignment at the granularity of windows) to extract the position IDs (windows) that appear with a threshold or more for all the cases and the window IDs associated with the position IDs (windows), and highlights and visualizes them by lining up the window IDs on one axis “
Tokudome discloses the limitations based on broadest reasonable interpretation in light of the specification – see page 6, 3rd paragraph - The main path generation unit 24a compares a plurality of operation paths Pa1 to Pa5 in the input order, identifies the input operations with the highest execution frequency in each of the first to third input orders, and connects them in a series. see page 6, 4th paragraph - As a "means for generating a subpath", the subpath generation unit 24b generates a subpath in which input operations that are executed less frequently than the input operations that form the main path in each input order are branched from the main path and connected (subpath). The editing distance is the number of input operation procedures that need to be modified so that the operation paths Pa1, Pa2, and Pa5 are the same as the main path. In this embodiment, the concept of editing distance is applied to generate a hierarchy of subpaths. As shown in FIG. 9, the operation path Pa1 is an input operation in which the black-painted portion is different, and the editing distance is “2”. Similarly, the editing distances of the operation paths Pa2 and Pa5 are both "1". see page 6, last paragraph - The path display unit 25 displays the main path generated by the main path generation unit 24a and the subpath generated by the subpath generation unit 24b in the path display area W105 of the business analysis program P as "means for displaying the main path and subpath". As shown in FIG. 7, the main path drawn in the path display area W105 is displayed – A-start… through D-end along an axis; see page 9, 3rd paragraph - According to the above embodiment, a plurality of operation paths can be specified from the actual operation log, which is useful in considering the introduction of RPA.), wherein
all nodes representing operation types are arranged in an array and the main flow having one or more nodes that exceeds the reference value is visualized as first visualization array and one or more nodes that do not exceed the reference value is visualized as second visualization array (Applicant’s [0095] as published – >80%, in eight out of 10 cases) are in the “main flow”; a second visualization for cases that do not satisfy the threshold; [0112] as published; [0160-0161] as published – “other than the main flow” in FIG. 34)).
Tokudome discloses the limitations based on broadest reasonable interpretation in light of the specification – see page 6, 3rd paragraph - The main path generation unit 24a compares a plurality of operation paths Pa1 to Pa5 in the input order, identifies the input operations with the highest execution frequency in each of the first to third input orders, and connects them in a series; page 6, 4th paragraph - the subpath generation unit 24b generates a subpath in which input operations that are executed less frequently than the input operations that form the main path in each input order are branched from the main path and connected (subpath). See FIG. 9-10); and
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display the one or more nodes that exceeds the reference value on a display (Oberman – see par 44 - , including one or more software programs 6 to operate and display a computer desktop system 7 (e.g. displayed as user interfaces such as a GUI); real-time (RT) local interface 8 executing on terminals 2 (e.g. a NICE Attended Robot provided by NICE, Ltd.) may execute an automation sequence in place of user input or provide or display a recommended next action to a user;
see also Tokudome – See page 2, 7th paragraph – “The output unit 4 is composed of a display device such as a liquid crystal display device that displays information output from the calculation unit 2.”; page 7, 3rd paragraph - Further options are provided for the display settings for the nodes N1 to N4, and the contents of the input operation can be easily grasped; see page 7, last paragraph - as shown in FIG. 10, the input operations C1 and C3 included in the first subpath (Pa2, Pa5) having the editing distance of "1" and the edge. E6 to E9 will be displayed as branched from the main path), in which the one or more nodes are displayed by respective window identification and position identification and one or more nodes that are below the reference value is displayed at different position (Oberman discloses the limitations based on broadest reasonable interpretation in light of the specification – see par 43 - input may be a log or database of desktop actions, e.g. user input or actions to a GUI for a variety of applications (disclosing a sequence based on granularity of windows and screens) performed by one or more employees. Data describing an action may include for example action data or input type descriptions (e.g. describing whether the input is via mouse or keyboard, or what type or input such as left click, right click, cut, paste, typing text), timestamp, application context, user name, screen window information such as title or name (e.g., as computer processes in this context may be displayed as windows, each window may have a title or name which may describe the user-facing application to which the user provides input), and where possible, field context; see par 60, FIG. 3 – suggest first action for automation sequence; In some embodiments, the first meaningful recorded action from the agent is suggested, for example the first recorded action that changes a GUI control state. see par 78 - A process may find a place to add a robust action by detecting two different consecutive actions, e.g. in the sequence the business analyst is creating that relate to the same element (or elements in the same hierarchy). A hierarchy of an object represents its position in the construction of the application in which the object resides. For example, in a Notepad application, a text area in which text is edited includes a Notepad Window control, which includes a Form control, which includes the text area: the hierarchy is the ordered list of objects in which any object is included;
see also Tokudome – page 3, last paragraph- page 4, 1st paragraph – The "object name" can be, for example, the "title text" displayed in the title bar of the web page when the object for which the input operation is performed is a web page displayed on the browser. The title text of the Web page can be obtained, for example, from the title of the header of the HTML file that constitutes the Web page. Further, when the object for which the input operation is performed is the screen of the application, it can be the "title text" displayed in the title bar of the screen. The title text of the application screen can be obtained, for example, from the file name.; page 6, 3rd paragraph - The main path generation unit 24a specifies the type and number of the first input operation B in the input order from the input operation A, the type and number of the second input operation C, and the type and number of the third input operation D. Specifically, the first input order is the input operations B1 and B2; see page 6, 4th paragraph - the editing distances of the operation paths Pa2 and Pa5 are both "1". Therefore, the subpath generation unit 24b generates the first subpath (Pa2, Pa5), the second subpath (Pa1), ..., The nth subpath (Pan) in ascending order of editing distance. The first to nth subpaths have a hierarchical structure showing the proximity to the main path; see page 7, 2nd paragraph - The application name, URL, or file path corresponding to the content of the input operation is displayed on the nodes N1 to N4; FIG. 8, “Application" W120 can specify an application to be displayed (on FIG. 8).)
Both Oberman and Tokudome are analogous art as they are directed to analyzing user performed operations for determining sequences of actions for automation (See Oberman Abstract, par 2-3 – automation for RPA (Robotic Process Automation); Tokudome Abstract, see page 9, 3rd paragraph – operation paths for introducing RPA). Oberman discloses an example of a sequence of actions forming a process in FIG. 2 (See par 35) where the Figure shows an axis, but it is not explicitly disclosed as being part of later embodiments. Oberman also discloses log of actions include screen window information, where title or name can be windows which describe user-facing applications (See par 43). Oberman discloses having a sequence of actions based on searching for best next actions to include and graphically showing the nodes/actions (608 in FIG. 6 – See par 100). Tokudome improves upon Oberman by disclosing while determining a “main path” of operations in a process and also discloses displaying the main path along an “axis” (See page 6, FIG. 7) and a subpath based on frequency (See page 6) along with visualizations of different paths along with a corresponding axis (See FIG. 9-10); and further where nodes can have its application name corresponding to the content displayed on the nodes (See page 6-7, FIG. 8). One of ordinary skill in the art would be motivated to display a path of actions for a sequence along an axis, where a main path is based on frequency of actions, as well as displaying application name on a node of the process to efficiently improve upon the sequence of actions that are best to include, and that have window or application context (See par 43) in Oberman (See FIG. 6, par 100) and the example (FIG. 2) that has an axis for a sequence of actions in Oberman.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the determined sequence of actions in Oberman, to further include an axis for a main path of actions and an axis for a subpath based on frequency of operations, that can include an application for the nodes where it is displayed in FIG. 8-10, as disclosed in Tokudome, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable and there is a reasonable expectation of success.
Concerning independent claim 6, Oberman and Tokudome disclose:
A visualization display method which is executed by a visualization display device (Oberman – see par 44 - A number of human users such as call-center agents may use agent terminals 2 which may be for example personal computers or terminals, including one or more software programs 6 to operate and display a computer desktop system 7 (e.g. displayed as user interfaces such as a GUI). In some embodiments, software programs 6 may display windows, e.g. via desktop system 7, and accept user input (e.g. via desktop system 7) and may interface with server software 22, e.g. receiving input from and sending output to software programs 6. see par 100 - FIG. 6 depicts a set of sequences and a search sequence, according to an embodiment of the present invention. A designed workflow or automation sequence 600 being created by a business analyst may have an SSTM 602 extracted, and used to search or mine for sequences; See par 105 - Embodiments of the invention may include one or more article(s) (e.g. memory 120 or storage 130) such as a computer or processor non-transitory readable medium, such as for example a memory, …encoding, including or storing instructions, e.g., computer-executable instructions, which, when executed by a processor or controller, carry out methods).
The remaining limitations are similar to claim 1 and are rejected for the same reasons as in claim 1.
It would be obvious to combine Oberman and Tokudome for the same reasons as claim 1.
Concerning independent claim 7, Oberman and Tokudome disclose:
A non-transitory computer-readable recording medium storing therein a visualization display program causing a computer (Oberman – See par 105 - Embodiments of the invention may include one or more article(s) (e.g. memory 120 or storage 130) such as a computer or processor non-transitory readable medium, such as for example a memory, …encoding, including or storing instructions, e.g., computer-executable instructions, which, when executed by a processor or controller, carry out methods; see par 108 - In other instances, well-known methods, procedures, and components, modules, units and/or circuits have not been described in detail so as not to obscure the invention) to execute a process comprising (Oberman – see par 44 - A number of human users such as call-center agents may use agent terminals 2 which may be for example personal computers or terminals, including one or more software programs 6 to operate and display a computer desktop system 7 (e.g. displayed as user interfaces such as a GUI). In some embodiments, software programs 6 may display windows, e.g. via desktop system 7, and accept user input (e.g. via desktop system 7) and may interface with server software 22, e.g. receiving input from and sending output to software programs 6. see par 100 - FIG. 6 depicts a set of sequences and a search sequence, according to an embodiment of the present invention. A designed workflow or automation sequence 600 being created by a business analyst may have an SSTM 602 extracted, and used to search or mine for sequences).
The remaining limitations are similar to claim 1 and are rejected for the same reasons as in claim 1.
It would be obvious to combine Oberman and Tokudome for the same reasons as claim 1.
Concerning claim 3, Oberman and Tokudome disclose:
The visualization display device according to claim 1, wherein the visualization display circuitry configured to further set a reference value of an operation to be visualized (Applicant’s [0071] as published - Further, the visualization unit 15c sets a reference value (threshold of operation) of an operation to be visualized
Oberman – see par 68 - A frequent sequential pattern may be a sequential pattern having a support (e.g. occurrence in a database, possibly divided by the total number of entries in the database) no less than a certain number or parameter (e.g. a minsup parameter)
See also Tokudome –see page 6, 3rd paragraph - The main path generation unit 24a compares a plurality of operation paths Pa1 to Pa5 in the input order, identifies the input operations with the highest execution frequency in each of the first to third input orders, and connects them in a series; see page 6, 4th paragraph - Generate subpaths of multiple layers according to edit distance, Levenshtein distance). The editing distance is the number of input operation procedures that need to be modified so that the operation paths Pa1, Pa2, and Pa5 are the same as the main path. In this embodiment, the concept of editing distance is applied to generate a hierarchy of subpaths. As shown in FIG. 9, the operation path Pa1 is an input operation in which the black-painted portion is different, and the editing distance is “2”. Similarly, the editing distances of the operation paths Pa2 and Pa5 are both "1". ),
arrange the nodes corresponding to the operation types of the main flow in a time series order on the one axis, among nodes corresponding to operation types that appear with the reference value or higher of the operation (Oberman – see par 67 - the search for action sequences corresponding to the SSTM may be performed via, for example, two operations. In the first phase or operation a sequential generator pattern mining algorithm generates candidate sequences from the initial sequence pool, via a mining operation, to create a set of best occurrences from the initial pool, typically without regard to the SSTM. This operation may produce a set of sequences which are a good representation of the input pool. For example, frequent sequential patterns generators may be found or discovered (e.g. mined) using a Frequent Sequential Generator Patterns (“FSGP”) process; see par 68 - A frequent sequential pattern may be a sequential pattern having a support (e.g. occurrence in a database, possibly divided by the total number of entries in the database) no less than a certain number or parameter (e.g. a minsup parameter).
See also Tokudome – see page 6, 3rd paragraph - The main path generation unit 24a compares a plurality of operation paths Pa1 to Pa5 in the input order, identifies the input operations with the highest execution frequency in each of the first to third input orders, and connects them in a series.), and
arrange and visualize nodes corresponding to operation types other than the operation types of the main flow in a time series order at positions different from on the one axis (Applicant’s specification [0096] as published states “Visualization processing of operations other than the main flow will be described with reference to FIG. 12. The visualization unit 15c visualizes operations other than the main flow.”
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Tokudome discloses the limitations based on broadest reasonable interpretation in light of the specification – see FIG. 9-10, see page 6, 4th paragraph - As a "means for generating a subpath", the subpath generation unit 24b generates a subpath in which input operations that are executed less frequently than the input operations that form the main path in each input order are branched from the main path and connected (subpath); Specifically, as shown in FIG. 9, the sub-path generation unit 24b sets the editing distance (for each of the operation paths Pa1, Pa2, Pa5) with respect to the main path “A .fwdarw. B2 .fwdarw. C2 .fwdarw. D” (operation paths Pa3, Pa4). Generate subpaths of multiple layers according to edit distance; page 6, last paragraph - The path display unit 25 displays the main path generated by the main path generation unit 24a and the subpath generated by the subpath generation unit 24b in the path display area W105 of the business analysis program P as "means for displaying the main path and subpath". (Main path drawing step, sub path drawing step); see page 7, last paragraph - For example, as shown in FIG. 10, the input operations C1 and C3 included in the first subpath (Pa2, Pa5) having the editing distance of "1" and the edge. E6 to E9 will be displayed as branched from the main path. Although not shown, if the slide bar W106 is further moved to the right one by one, input operations after the second subpath whose editing distance is larger than "2" are added step by step to draw).
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It would be obvious to combine Oberman and Tokudome for the same reasons as claim 1. In addition, Oberman discloses analyzing candidate sequences based on distance (See par 95-98). Tokudome improves upon Oberman by disclosing having a main path and visualizing other nodes at other positions.
Concerning claim 4, Oberman and Tokudome disclose:
The visualization display device according to claim 1, wherein the visualization display circuitry configured to:
further generate an operation sequence in units of windows arrayed in a time series order for each case (Oberman – see par 35 - FIG. 2 is an example of a sequence of actions forming a process according to embodiments of the present invention. Referring to FIG. 2, actions A, G, H and X are business process actions are performed on screen elements, such as entering text to a field. See par 40 - technologies exist to obtain high-level system-specific event logs as input data, such as case ID (e.g. “Process ID”), activity ID and, timestamp to identify user activity or input. A case ID may identify the process instance and an activity ID may specify the task that has been performed as part of the process; see par 53-54 – building automation workflow or automation sequence by identifying sequences (e.g. series of actions identified as business processes). See par 61 - In operation 216, a next action may be found for suggestion. The set of actions from the sequence the business analyst is creating, a segment of cut-out actions segment from the workflow, may be termed search-sequence-to-match (“SSTM”). See par 72 - In the second phase or operation, the SSTM may be used to search over the resultant candidate sequences, e.g. by aligning the SSTM and measuring a distance to each candidate sequence.) and aligns the operation sequence in units of windows (Oberman – see par 39 - In contrast, the low level event data recorded and used in embodiments of the present invention may not be associated with a specific process (e.g. case ID) or activity but rather may be associated only with a window which has a name and with a program or application operating the window (e.g. an internet browser). The title (e.g., the label displayed at the top) of the screen window, and the name of the program executing with which the user is interacting are data may be extracted or obtained; see par 43 - input may be a log or database of desktop actions, e.g. user input or actions to a GUI for a variety of applications (disclosing a sequence based on granularity of windows and screens) performed by one or more employees. Data describing an action may include for example action data or input type descriptions, timestamp, application context, user name, screen window information such as title or name (e.g., as computer processes in this context may be displayed as windows, each window may have a title or name which may describe the user-facing application to which the user provides input), and where possible, field context (disclosing a sequence based on granularity of windows and screens). see par 61 - The set of actions from the sequence the business analyst is creating, a segment of cut-out actions segment from the workflow, may be termed search-sequence-to-match (“SSTM”). for example, the last several (e.g. 3, 4 or 5) actions, possibly defined by a window, may be selected as the set. see par 72 - In the second phase or operation, the SSTM may be used to search over the resultant candidate sequences, e.g. by aligning the SSTM and measuring a distance to each candidate sequence. see par 93 - In operation 506 the candidate sequences found or mined in operation 504 may be filtered and an alignment score or rating determined), and
specify windows that appear with a threshold or more at the same position in the operation sequence in units of windows of each case as windows of the main flow on the basis of the aligned operation sequence in units of windows (Oberman – see par 22 - Each low-level user action may be described in a database by several fields of the action data such as action time, user details, action details, window name and size, program executing the window, and whether or not text was entered. A generalized name or description may also be created and associated with the action, at various points in the processes described (e.g. for processing a general database of user actions, or for processing a set of actions; see par 61 - The set of actions from the sequence the business analyst is creating, a segment of cut-out actions segment from the workflow, may be termed search-sequence-to-match (“SSTM”). For example, the last several (e.g. 3, 4 or 5) actions, possibly defined by a window, may be selected as the set. In one embodiment, the last action in the sequence may be the last designed or added action by the business analyst, the other actions in the set may be found by counting backwards from this last designed action and including the actions in this window. see par 67 - the search for action sequences corresponding to the SSTM may be performed … For example, frequent sequential patterns generators may be found or discovered (e.g. mined) using a Frequent Sequential Generator Patterns (“FSGP”) process; see par 68 - A frequent sequential pattern may be a sequential pattern having a support (e.g. occurrence in a database, possibly divided by the total number of entries in the database) no less than a certain number or parameter (e.g. a minsup parameter).
See also - Tokudome see page 6, 3rd paragraph - The main path generation unit 24a compares a plurality of operation paths Pa1 to Pa5 in the input order, identifies the input operations with the highest execution frequency in each of the first to third input orders, and connects them in a series. B2 .fwdarw. C2 .fwdarw. D ”is generated; page 6, 4th paragraph - as shown in FIG. 9, the sub-path generation unit 24b sets the editing distance (for each of the operation paths Pa1, Pa2, Pa5) with respect to the main path),
arrange nodes corresponding to the windows of the main flow in a time series order on one … (Oberman – see par 61 - The set of actions from the sequence the business analyst is creating, a segment of cut-out actions segment from the workflow, may be termed search-sequence-to-match (“SSTM”). For example, the last several (e.g. 3, 4 or 5) actions, possibly defined by a window, may be selected as the set. In one embodiment, the last action in the sequence may be the last designed or added action by the business analyst, the other actions in the set may be found by counting backwards from this last designed action and including the actions in this window. See par 88, 92 - In operation 408, a set of actions may be selected or extracted according to a moving or rolling window of X (e.g. five) actions to be used to search to form an SSTM. A moving or rolling window may be defined by X (e.g. a pre-configured integer), actions taken from the designed workflow.
“on one axis” Tokudome – see page 6, 3rd paragraph - The main path generation unit 24a has a function of generating a main path from a plurality of operation paths specified by the operation path identification unit 23 as a "means for generating a main path" (main path generation step). Here, as an example, it is assumed that the operation paths Pa1 to Pa5 are specified by the operation path identification unit 23 as shown in FIG. The main path generation unit 24a specifies the type and number of the first input operation B in the input order from the input operation A, the type and number of the second input operation C, and the type and number of the third input operation D.),
arrange nodes corresponding to windows other than the windows of the main flow in a time series order at positions different from on the one axis (Oberman – see par 92 - In operation 502 a set of actions is selected from automation sequence 500′, e.g. using a rolling window of the last X actions, to produce SSTM 502′.
See Tokudome – See page 6, Operation path generator, 4th paragraph - As a "means for generating a subpath", the subpath generation unit 24b generates a subpath in which input operations that are executed less frequently than the input operations that form the main path in each input order are branched from the main path and connected (subpath); Specifically, as shown in FIG. 9, the sub-path generation unit 24b sets the editing distance (for each of the operation paths Pa1, Pa2, Pa5) with respect to the main path “A .fwdarw. B2 .fwdarw. C2 .fwdarw.D” (operation paths Pa3, Pa4). Generate subpaths of multiple layers according to edit distance, Levenshtein distance). The editing distance is the number of input operation procedures that need to be modified so that the operation paths Pa1, Pa2, and Pa5 are the same as the main path; see FIG. 10 – showing main path with central axis; showing “different “axis” for either C1 or C3 nodes), and
superimpose and visualize nodes corresponding to operations of each window (Oberman – FIG. 6 – nodes for “probable routine”
See also Tokudome FIG. 7 (for main flow), FIG. 10 (for main flow AND subpaths which discloses “positions difference from on the one axis”)).
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It would be obvious to combine Oberman and Tokudome for the same reasons as claim 1 and claim 3.
Concerning claim 5, Oberman and Tokudome disclose:
The visualization display device according to claim 4, wherein the visualization display circuitry configured to further set a reference value of a window to be visualized (Oberman – see par 68 - A frequent sequential pattern may be a sequential pattern having a support (e.g. occurrence in a database, possibly divided by the total number of entries in the database) no less than a certain number or parameter (e.g. a minsup parameter); see par 88 - In operation 408, a set of actions may be selected or extracted according to a moving or rolling window of X (e.g. five) actions to be used to search to form an SSTM. A moving or rolling window may be defined by X (e.g. a pre-configured integer), actions taken from the designed workflow. see par 95-98 – candidate sequences selected on composite score or rating (based on distance between vector representation of SSTM and candidate sequence);
See also Tokudome – see page 6, 3rd paragraph - The main path generation unit 24a compares a plurality of operation paths Pa1 to Pa5 in the input order, identifies the input operations with the highest execution frequency in each of the first to third input orders, and connects them in a series. see page 6, 4th paragraph - Generate subpaths of multiple layers according to edit distance, Levenshtein distance). The editing distance is the number of input operation procedures that need to be modified so that the operation paths Pa1, Pa2, and Pa5 are the same as the main path. In this embodiment, the concept of editing distance is applied to generate a hierarchy of subpaths. As shown in FIG. 9, the operation path Pa1 is an input operation in which the black-painted portion is different, and the editing distance is “2”. Similarly, the editing distances of the operation paths Pa2 and Pa5 are both "1"),
arrange nodes corresponding to the windows of the main flow in a time series order on one axis, among nodes corresponding to windows that appear with the reference value or higher of the window (Oberman – see par 67 - the search for action sequences corresponding to the SSTM may be performed via, for example, two operations. In the first phase or operation a sequential generator pattern mining algorithm generates candidate sequences from the initial sequence pool, via a mining operation, to create a set of best occurrences from the initial pool, typically without regard to the SSTM. This operation may produce a set of sequences which are a good representation of the input pool. For example, frequent sequential patterns generators may be found or discovered (e.g. mined) using a Frequent Sequential Generator Patterns (“FSGP”) process; see par 68 - A frequent sequential pattern may be a sequential pattern having a support (e.g. occurrence in a database, possibly divided by the total number of entries in the database) no less than a certain number or parameter (e.g. a minsup parameter).
See also Tokudome – see page 6, 3rd paragraph - he main path generation unit 24a has a function of generating a main path from a plurality of operation paths specified by the operation path identification unit 23 as a "means for generating a main path" (main path generation step). Here, as an example, it is assumed that the operation paths Pa1 to Pa5 are specified by the operation path identification unit 23 as shown in FIG. The main path generation unit 24a specifies the type and number of the first input operation B in the input order from the input operation A, the type and number of the second input operation C, and the type and number of the third input operation D. .. Specifically, the first input order is the input operations B1 and B2, and the frequency of their execution is highest when B2 is four times), and
arrange and visualize nodes corresponding to windows other than the windows of the main flow in a time series order at positions different from on the one axis (Tokudome discloses the limitations based on broadest reasonable interpretation in light of the specification – see FIG. 9-10, page 6, 4th paragraph - Specifically, as shown in FIG. 9, the sub-path generation unit 24b sets the editing distance (for each of the operation paths Pa1, Pa2, Pa5) with respect to the main path “A .fwdarw. B2 .fwdarw. C2 .fwdarw. D” (operation paths Pa3, Pa4). Generate subpaths of multiple layers according to edit distance; page 6, last paragraph - The path display unit 25 displays the main path generated by the main path generation unit 24a and the subpath generated by the subpath generation unit 24b in the path display area W105 of the business analysis program P as "means for displaying the main path and subpath". (Main path drawing step, sub path drawing step); see page 7, last paragraph - For example, as shown in FIG. 10, the input operations C1 and C3 included in the first subpath (Pa2, Pa5) having the editing distance of "1" and the edge. E6 to E9 will be displayed as branched from the main path. Although not shown, if the slide bar W106 is further moved to the right one by one, input operations after the second subpath whose editing distance is larger than "2" are added step by step to draw)).
It would be obvious to combine Oberman and Tokudome for the same reasons as claim 1 and claim 3.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Oberman (US 2022/0044168), and Tokudome (WO 2020/204144), as applied to claims 1 and 3-7 above, and further in view of Ma (US 2020/0206920).
Concerning claim 2, Oberman and Tokudome disclose:
The visualization display device according to claim 1, wherein the visualization display circuitry configured to specify operations of the same type by extracting information on operation locations from the operation log (Oberman – see par 57 - Optionally, a context for the action may be inferred by using a Word2Vec process on neighboring actions as they appear everywhere in the overall dataset. Segmenting may be performed, splitting an input stream of actions into “sentences” of actions, or other actions that are temporally linked so that the sentence describes a particular business functionality. See par 58 - segmenting may include splitting a series of user actions into a number of user action sentences, each of the user action sentences identifying a functionality executed by the user via a computer. A sequence of user actions in the user action sentences may be determined based on a recurrence for the sequence in the user action sentences, where the sequence includes reoccurring user actions from the user actions recurring in the user action sentences),
align the operation sequence in units of operations through pairwise alignment (Oberman – see par 72 - the SSTM may be used to search over the resultant candidate sequences, e.g. by aligning the SSTM and measuring a distance to each candidate sequence; see par 73-74 - a. Alignment score (e.g. a measure of how well the returned sequence aligns with the SSTM; see par 93 - Each remaining candidate sequence (after filtering) may be aligned to SSTM 502′ and may receive an alignment score or rating that rates how well each sequence matches the sequence in SSTM 502′. In one embodiment, an alignment score or rating S.sub.alg is according to example Eq. 1, where gap penalties is a measure of gaps or spacing between actions in one of the two sequences being compared, the gaps separated by actions not in the other sequence; identities measures the number of actions in order that occur in each sequence; and mismatches measures the number of actions in order in each sequence that are not in the other sequence;
see also Ma – see par 163 – a distance matrix is computed for all pairs of subsequences; see par 165 - each subsequence pair being characterized by a distance d.sub.i between two respective subsequences forming the subsequence pair; see par 177-178 – align events by distance),
generate a distance matrix for each operation sequence in units of operations (Oberman – see par 95 - A distance, e.g. a mathematical representation of difference between the entities, may be calculated between SSTM 502′ and each of the candidate sequences. For example, the cosine distance between the vector representation of SSTM 502′ and that of each candidate sequence may be calculated.)
To any extent Oberman does not disclose “matrix”, Ma discloses:
generate a distance “matrix” for each operation sequence in units of operations (Ma see par 163 - Regardless of the particular manner in which feature vectors are generated, a distance matrix is computed for all pairs of subsequences. The preferred metric for the distance given the calculation of the feature vectors as described above is the Euclidean distance; however, other distance metrics can also be of value, for instance the cosine similarity, or the Levenshtein distance if the feature vectors are understood to be directly word sequences in the event language).
Oberman, Tokudome, and Ma disclose:
generate a distance vector using the distance matrix (Oberman – see par 73 - In the second phase or operation, the SSTM may be used to search over the resultant candidate sequences, e.g. by aligning the SSTM and measuring a distance to each candidate sequence. [0073] As part of operation 216, the list of results may be ranked or ordered, for example by factors such as the following non-limiting examples: [0074] a. Alignment score (e.g. a measure of how well the returned sequence aligns with the SSTM); [0075] b. Embedded routine vector cosine distance (e.g. distance from the SSTM); and/or [0076] c. FSGP support score, as described elsewhere herein. See par 95 - A distance, e.g. a mathematical representation of difference between the entities, may be calculated between SSTM 502′ and each of the candidate sequences. For example, the cosine distance between the vector representation of SSTM 502′ and that of each candidate sequence may be calculated. In one embodiment, the distance between a candidate sequence, SubSeq, and SSTM 502′ may be calculated using the known cosine similarity measure, a measure of similarity between two vectors calculated by determining the angle between the vectors, where the distance may be 1-similarity;
See also Ma – See par 161 - The concatenated event streams are parsed into subsequences using the sliding window length N and feature vectors are calculated for each subsequence starting at each position within the event stream; See par 162 - ] Preferably, the feature vectors are calculated using a known auto-encoder and yield dense feature vectors for each window, e.g. vectors having a dimensionality in a range from about 50 to about 100 for a window length of about 30 events per subsequence.), and
further align the operation sequence through multiple sequence alignment in the order of the operation sequence in units of operations having the smaller distance vector (Ma see par 163 - Clusters of non-overlapping subsequences may then be identified according to similarity. For example, a predetermined set k of pairs of subsequences characterized by the smallest distances between the elements of the pairs among the overall distance matrix may be selected as initial clusters representing k task types. See par 168 - In this process, an additional subsequence may only be added to an existing cluster when the distance to an element of said cluster is small. Small in this case, assuming Euclidean distances contained in the distance matrix, means preferably at least about 3 standard deviations smaller than the median distance between the cluster and all other subsequences).
Oberman, Tokudome, and Ma are analogous art as they are directed to analyzing user performed operations for determining sequences of actions for automation (See Oberman Abstract, par 2-3 – automation for RPA (Robotic Process Automation; Tokudome Abstract, see page 9, 3rd paragraph – operation paths for introducing RPA; Ma Abstract). Oberman discloses calculating distance between candidate sequences (See par 95). Tokudome discloses calculating distances between path of operations (See page 6, 4th paragraph). Ma improves upon Oberman and Tokudome by disclosing a matrix, analyzing alignment from pairs, and aligning by adding subsequences by considering ones with smallest distance. One of ordinary skill in the art would be motivated to have a matrix and adding subsequences to clusters based on smallest distances to efficiently improve upon the sequence of actions that are best to include and considering distance and distance vectors in Oberman (See FIG. 6, par 100) and the calculation of distances between path of operations in Tokudome.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the determined sequence of actions in Oberman, to further include an axis for a main path of actions as disclosed in Tokudome, to further include distances, matrix, and adding subsequences with the smallest distance as disclosed in Ma, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable and there is a reasonable expectation of success.
Response to Arguments
Applicant's arguments filed 3/1/26 have been fully considered but they are not persuasive and/or are moot in view of the new rejections.
With regards to 101, Applicant argues that that the claim limitations cannot be practically performed in the human mind, so they do not recite a mental process. Remarks, page 7-8. In response, Examiner respectfully disagrees. First, the 101 rejection is revised. Second, the 101 rejection did not place the current claims in the “Mental process” grouping. Rather, it is in the grouping of “Certain Methods of Organizing Human Activity” (to show people an order of operations for a business process, such as A-B-C-D) and “Mathematical Relationships” (comparing to a threshold number (e.g. frequency/occurrences) of past operations in history).
Applicant then argues that the new limitation of “align the operation sequence based on a granularity of windows, wherein a set of the operation sequence is processed at the granularity of screens” cannot be practically performed in the human mind. Remarks, page 8. In response, Examiner respectfully disagrees. First, the 101 rejection is revised. Second, the 101 rejection did not place the current claims in the “Mental process” grouping. Rather, it is in the grouping of “Certain Methods of Organizing Human Activity” (to show people an order of operations for a business process, such as A-B-C-D) and “Mathematical Relationships” (comparing to a threshold number (e.g. frequency/occurrences) of past operations in history). Third, the claim is referring to the history log sequence including information relative to windows and screens. See for example Applicant’s FIGS. 13, 33-34. The claim is directed to certain methods of organizing human activity as it covers the business process of forming a representative business process of historical steps. The history includes the steps being relative to a window. In addition, this is viewed as grouping by frequency occurrences for each “type” of window/screen. See e.g. Applicant’s [0067] as published “window information related to a user’s operation, a GUI component name.”
With regards to Step 2a, prong two, Applicant then argues that the claims are a practical application for improving the computer or another technology under MPEP 2106.04(a) because the claim is “align the operation sequence based on a granularity of windows, wherein a set of the operation sequence is processed at the granularity of screens” to improve the accuracy of the main process identification. Remarks, page 8. In response, Examiner respectfully disagrees. The arguments are moot in view of the revised rejection necessitated by the amendments. Nonetheless, the current claims are not viewed as a practical application as it merely displays the result of the analysis – grouping by names of windows/screens/programs a user historically uses. Claim 1 has additional elements such as “on a display”, but all it is displaying are different representations of business process flows or sequences. Unfortunately, upon further review, the “granularity” is given in Applicant’s example as to “how specific” is the business process. Applicant’s [0157] as published states “FIG. 33. The visualization unit 15c uses the alignment result (the result of alignment at the granularity of windows) to extract the position IDs (windows) that appear with a threshold or more for all the cases and the window IDs associated with the position IDs (windows), and highlights and visualizes them by lining up the window IDs on one axis in the order of the position IDs (windows).” The business process here, as gathered from a log of historical user operations, is at the “granularity” of windows/screens used, where the method and other claims cover certain methods of organizing human activity, of using rules for what is in the business process, where the business process is aligned at the “granularity” (i.e. specificity) of windows/screens used by users in the historical log.
Applicant then argues that the claims are eligible under step 2B because it is computer-centric in the display. Remarks, page 9-10. In response, Examiner respectfully disagrees. The arguments are moot in view of the revised rejection necessitated by the amendments. Nonetheless, just having a computer that “displays” the results, as currently claimed here, is not sufficient. As one example, this is not sufficient to improving the GUI, improving navigation in the GUI, such as example of improved computer-functionality MPEP 2106.05(a)(I)(x) “An improved user interface for electronic devices that displays an application summary of unlaunched applications, where the particular data in the summary is selectable by a user to launch the respective application. Core Wireless Licensing S.A.R.L., v. LG Electronics, Inc., 880 F.3d 1356.” See also MPEP 2106.05(f) “ in Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017), the steps in the claims described "the creation of a dynamic document based upon ‘management record types’ and ‘primary record types.’" 850 F.3d at 1339-40; 121 USPQ2d at 1945-46. The claims were found to be directed to the abstract idea of "collecting, displaying, and manipulating data." 850 F.3d at 1340; 121 USPQ2d at 1946.
With regards to 103, Applicant’s arguments are moot in view of the new citations necessitated by the amendments.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Tanaka (JP 2015232749) – directed to sequence pattern 41 (in 708 of FIG. 10) appears more frequently than other sequence patterns is the main flow in the business flow (see page 10, last paragraph, FIG. 10).
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/IVAN R GOLDBERG/Primary Examiner, Art Unit 3619
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