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 .
DETAILED ACTION
This action is in response to the application filed 09/19/2025.
Claims 1 - 22 are pending and have been examined.
Claims 1 - 22 are rejected.
Response to Arguments
Applicant’s arguments with respect to claim(s) below have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
In service to Applicant, Examiner adds explanation of the interpretation of the claimed “preview”.
Examiner has reviewed the specification of the present application and also in the claims for a clear definition of a “preview” without success. The only limitation that can be found is in claim 1 where it states a preview includes attributes of an expanded view dataset and that a preview is generated from a subset of data related to the base dataset. Finally, an input may be received that specified one or more fields that are included in the “preview” and a dataset that is based on available dataset with “the input” is generated.
Reynolds provide various types of previews including a preview (Reynolds [0138: “According to some examples, a data preview of subsets of data may be presented in the user interface, the data preview showing portions of a dataset or set of data. A data preview may be generated (e.g., by a user interface element generator) to depict each subset of data as a column of data.”]) and also a derivative set (Reynolds [0125: “An overlay interface 1210 may be presented over collaborative dataset interface 1202, with a proposed derived dataset attribute “Zip Code.” If the inference or prediction is adequate, then an annotation directed to “zip code” may be generated (e.g., semi-automatically) upon accepting the derived dataset attribute at input 1271.”]). Here attributes generated by the derived dataset is selected by the user to be included with the base dataset.
Although Reynolds specifically teaches a use of previews, it does not explicitly teach selection from a preview to include in a newly generated dataset.
However, combining the teaching of Reynolds and Miller, it at least suggests to one of ordinary skill in the art before the effective filing date, that one can select attributes to generate a dataset.
The rationale is further provided below, but in short, as shown in figures 6B and 14, a selection can be made from a table (Miller [0157-0162]). See below.
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
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 1-22 are rejected under 35 U.S.C. 103 as being unpatentable over Reynolds et al. (US 20210019327; “Reynolds” hereinafter), in view of Convertino et al. (US 20160328406; “Convertino” hereinafter), and further in view of Miller et al. (US 20150154269; “Miller” hereinafter).
As per claim 1, Reynolds discloses A method implemented by a data processing system for: enabling a user to preview attributes of fields of an expanded view of a base dataset (Reynolds [0125: “As shown, collaborative dataset interface 1202 is configured to present a data preview 1204 of the set of data 1201a (or dataset thereof), with “???” indicating that a description or annotation is not included.” And 0049 discussing attribute expansion.]) and to specify one or more of the fields to use in downstream data processing and generating a dataset that includes the one or more of the fields from the preview specified to be used in the downstream data processing, with the generated dataset having increased efficiency with respect to speed and data memory, relative to an efficiency of generating a dataset including all the fields of the expanded view when only the specified one or more of the fields are used in the downstream data processing, method including (Reynolds [0045-0049: 0045: dataset creation and data interoperability, 0047: linking datasets, 0048: dataset attributes identified, 0049: access attributes.]):
receiving an identification of a base dataset (Reynolds [0049: “ Therefore, user 108a may enter search terms into the search field 121 to search for any relevant datasets that may augment or otherwise supplement a current collaborative dataset.”]),
based on the identification, receiving a definition of an expanded view dataset, wherein the definition of the expanded view dataset specifies other datasets related to the base dataset or fields of other datasets related to the base dataset (Reynolds [0049: “Therefore, user 108a may enter search terms into the search field 121 to search for any relevant datasets that may augment or otherwise supplement a current collaborative dataset.”]; [0130; 0138: “The correlated attributes, as generated by attribute correlator 1263, may facilitate the use of derived data or link-related data, as attributes, to form associate, combine, join, or merge datasets to form collaborative datasets.”]),
[based on the definition of the expanded view dataset], outputting a preview of attributes of fields of the expanded view dataset , wherein the preview is generated from a subset of data in the other datasets related to the base dataset or in the fields of the other datasets related to the base dataset (Reynolds [0125: “Also, a dataset attribute, datatype, a data classification, etc. may be derived based on, for example, data from user interface data 1292 (e.g., based on data representing an annotation entered via user interface 1202). As shown, collaborative dataset interface 1202 is configured to present a data preview 1204 of the set of data 1201a (or dataset thereof), with “???” indicating that a description or annotation is not included.”]; [See figure 12 and 0138: “According to some examples, a data preview of subsets of data may be presented in the user interface, the data preview showing portions of a dataset or set of data. A data preview may be generated (e.g., by a user interface element generator) to depict each subset of data as a column of data. In one example, a data view of a column of data may be presented with an unknown dataset attribute, whereby data may be received to annotate a column header to form an annotation to resolve the unknown dataset attribute. The annotation may refer to a datatype, a data classification, or the like.”]),
[receiving input that specifies one or more of the fields from the preview] to be available for data processing, and [based on the input that specifies the one or more of the fields from the preview, generating an available dataset] that includes data in the base dataset and data in the one or more of the fields specified (Reynolds [0125, 0134, 0138-0139: “For example, input 1371 may be activated to add derived column 1392 to the dataset. Input 1373 may be activated to substitute and replace columns 1306a and 1306b with derived column 1392.”]).
Although Reynolds teaches using definition for creating views, Reynolds does not explicitly teach, however, Cnvertino teaches based on the definition of the expanded view dataset (Convertino [0121-0122; 0144: “A Dataset is a class that abstracts a file, table, view, etc. of interest to a user. A DataElement is a class that abstracts a column of a dataset of interest to a user.”33]; [0061: “Knowledge base 130 also maintains relationships between data elements and data definitions which represent the semantics of the data element, e.g., where two particular datasets both contain the same specific type of data, or a column with the same set (or overlapping sets) of values (i.e., all the value can be checked against a common reference table).”]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate the use of definition related to an expanded view of Convertion into the view generator and interface of Reynolds to produce an expected result of using definitions to provide expanded views. The modification would be obvious because one of ordinary skill in the art would be motivated to use a definition-based system and method to generate a view of data.
Although Reynolds teaches using previews and field selections, Reynolds does not explicitly teach, however, Miller in an analogous art teaches receiving input that specifies one or more of the fields from the preview [to be available for data processing, and] based on the input that specifies the one or more of the fields from the preview, generating an available dataset (Miller [0157-0162: “FIG. 14 illustrates a portion of a GUI that previews results of applying an extraction rule formulated using multiple example events and positive examples of values to select.” . . . “For example, a user can select two or more objects where an object is either an existing field, or a selection of text within an existing field (a selection of text within an existing field is essentially a secondary extraction) with the intention of creating a new field.”]; [0294-0299]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate the attribute selection from a table and previews of Miller into the materialized view generating module of Reynolds to produce an invention with an expected success of selecting from a preview attributes to based logic for generation of a dataset. The modification would be obvious because one of ordinary skill in the art would be motivated to provide users with a tool that assists users understand data and develop useful schemas (Miller [0007-0008]).
As per claim 2, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, further including:
providing the preview of the attributes of the expanded view dataset, with the expanded view dataset, when generated, including data from the base dataset and the other datasets related to the base dataset (Reynolds [0125 and see figures 12 and 16]).
As per claim 3, rejection for claim 2 is incorporated and further Reynolds discloses The method of claim 2 wherein the definition of the expanded view dataset specifies a set of data processing operations performed to generate the expanded view dataset that includes the data from the base dataset and the other datasets related to the base dataset (Reynolds [0138: “According to some examples, a data preview of subsets of data may be presented in the user interface, the data preview showing portions of a dataset or set of data. A data preview may be generated (e.g., by a user interface element generator) to depict each subset of data as a column of data. In one example, a data view of a column of data may be presented with an unknown dataset attribute, whereby data may be received to annotate a column header to form an annotation to resolve the unknown dataset attribute.” And see figure 12 label 1210.]; [0125: Annotating]; [0183: “Activation of user input 2589 may cause the presentation of data preview 2511 to transition to user interface 2402 or data arrangement overview interface 2411 of FIG. 25.”]), and
wherein the preview is generated from applying the set of data processing operations specified by the definition of the expanded view dataset to only a subset of the data in the base dataset and the other datasets related to the base dataset (Reynolds [0099: Operations are illustrated.]; [0125: Annotation]).
As per claim 4, rejection for claim 2 is incorporated and further Reynolds discloses The method of claim 2, further including:
responsive to providing the preview, receiving a specification that specifies data processing operations, wherein a data processing operation of the specification is at least partly defined based on user input that identifies an attribute included in the preview as an attribute of that data processing operation (Reynolds [0125: “Also, a dataset attribute, datatype, a data classification, etc. may be derived based on, for example, data from user interface data 1292 (e.g., based on data representing an annotation entered via user interface 1202). As shown, collaborative dataset interface 1202 is configured to present a data preview 1204 of the set of data 1201a (or dataset thereof), with “???” indicating that a description or annotation is not included.”]; [See figure 12 and 0138: “According to some examples, a data preview of subsets of data may be presented in the user interface, the data preview showing portions of a dataset or set of data. A data preview may be generated (e.g., by a user interface element generator) to depict each subset of data as a column of data. In one example, a data view of a column of data may be presented with an unknown dataset attribute, whereby data may be received to annotate a column header to form an annotation to resolve the unknown dataset attribute. The annotation may refer to a datatype, a data classification, or the like.”]).
As per claim 5, rejection for claim 3 is incorporated and further Reynolds discloses The method of claim 3, further including:
based on the data processing operation that is at least partly defined based on the user input that identifies the attribute included in the preview as the attribute of that data processing operation, updating the set of data processing operations of the definition by applying one or more optimization rules to the set of data processing operations (Reynolds [0125-0126: “In some examples, data enrichment manager 1236 may include logic to determine the applicability of a specific one of dataset attributes 1254a and 1254b based on the context.”, 0135: Where functions are to optimize data handling.]), and executing the updated set of data processing operations to generate a dataset that includes only a subset of data that would have been included in the expanded view dataset (Reynolds [0076: “Further, collaboration manager 460 may be configured to monitor updates to dataset attributes to disseminate the updates to a community of networked users or participants. Therefore, users 408a and 408b, as well as any other user or authorized participant, may receive communications (e.g., via user interface) to discover new or recently-modified dataset-related information in real-time (or near real-time).” . . . 0143: “In this example, dataset attribute manager 1761 is configured to monitor updates and changes to various subsets of data representing dataset attribute data 1734a and various subsets of data representing user attribute data 1734b, and to identify such updates and changes.”]).
As per claim 6, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, further including:
enabling a user to register a definition of a new dataset with a data catalog (Reynolds [0120: “Data and datasets may be enhanced, modified or annotated based on contextual data, such as data-related characteristics (e.g., type of data, qualities and quantities of data accesses, including queries, purpose or objective of datasets, such as deriving vaccines for Zika virus, etc.), time of day, user-related characteristics (e.g., type of user, demographics of user, citizenship of user, location of user, etc.), and other contextually-related characteristics that may guide creation of a dataset or the linking thereof.”]), wherein the definition of the new dataset specifies a selected dataset and other datasets related to the selected dataset, wherein the definition provides for logical access of the other datasets related to the base dataset without incurring a computational cost of providing data in the other related datasets (Reynolds [0122-0125, 0130: where linking datasets are illustrated: “Thus, the “postal code,” as a “derived annotation,” may be linked to the classification of “numeric” at layer one 1252. In turn, layer one 1252 data may be linked to 5 digits in a column at layer zero 1251).”]).
As per claim 7, rejection for claim 6 is incorporated and further Reynolds discloses The method of claim 6, further including:
accessing a data catalog specifying one or more datasets, and providing a user interface indicating that the one or more datasets are candidates for generating the expanded view dataset (Reynolds [0055: “Insight information presented in a user interface (e.g., responsive to dataset creation) may describe various aspects of a dataset, in summary form, such as, but not limited to, annotations (e.g., of columns, cells, or any portion of data), data classifications (e.g., a geographical location, such as a zip code, etc.), datatypes (e.g., string, numeric, categorical, Boolean, integer, etc.), a number of data points, a number of columns, a “shape” or distribution of data and/or data values, a number of empty or non-empty cells in a tabular data structure, a number of non-conforming data (e.g., a non-numeric data value in column expecting a numeric data, an image file, etc.) in cells of a tabular data structure, a number of distinct values, etc.”]; [See figure 21 where link is expanded.]; [0137: “Derived columns 1504, 1506, and 1508 may also be presented in user interface 1502. Derived columns 1504, 1506, and 1508 may be viewed as expanded versions of column 1522, according to some examples.” See with figures 14-15]; [0136-0138: User interface]).
As per claim 8, rejection for claim 7 is incorporated and further Reynolds discloses The method of claim 7, further including: receiving, through the user interface, an indication of a particular dataset as the base dataset, and responsive to the indication, automatically generating a definition of the expanded view dataset for the particular dataset (Reynolds [0125: “As shown, collaborative dataset interface 1202 is configured to present a data preview 1204 of the set of data 1201a (or dataset thereof), with “???” indicating that a description or annotation is not included.”]; [0130; 0138: “The correlated attributes, as generated by attribute correlator 1263, may facilitate the use of derived data or link-related data, as attributes, to form associate, combine, join, or merge datasets to form collaborative datasets.”]).
As per claim 9, rejection for claim 8 is incorporated and further Reynolds in view of Convertino discloses The method of claim 8, further including: identifying the particular dataset as the base dataset and one or more attributes of the particular dataset, determining, from the one or more attributes, a definition of the base dataset, based on the definition of the base dataset, determining, the one or more other datasets that are related to the base dataset (Reynolds [0045-0049: 0045: dataset creation and data interoperability, 0047: linking datasets, 0048: dataset attributes identified, 0049: access attributes.]), and based on the determined one or more other datasets, generating the definition of the expanded view dataset that specifies the base dataset, the one or more other datasets and one or more relationships among the base dataset and the one or more other datasets (Reynolds [0049: “Therefore, user 108a may enter search terms into the search field 121 to search for any relevant datasets that may augment or otherwise supplement a current collaborative dataset.”]; [0130; 0138: “The correlated attributes, as generated by attribute correlator 1263, may facilitate the use of derived data or link-related data, as attributes, to form associate, combine, join, or merge datasets to form collaborative datasets.”] and in view of Convertino [0121-0122; 0144: “A Dataset is a class that abstracts a file, table, view, etc. of interest to a user. A DataElement is a class that abstracts a column of a dataset of interest to a user.”33]; [0061: “Knowledge base 130 also maintains relationships between data elements and data definitions which represent the semantics of the data element, e.g., where two particular datasets both contain the same specific type of data, or a column with the same set (or overlapping sets) of values (i.e., all the value can be checked against a common reference table).”]).
As per claim 10, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, further including: storing, in a hardware storage device, the definition of the expanded view dataset, and registering the definition of the expanded view dataset with a data catalog (Convertino [0125 and see “Table 1” where catalog is described: “Recommender system 120 processes these key words and searches them against the various datasets (e.g., the database tables and associated metadata stored in knowledge base 130) for matching datasets.”]).
As per claim 11, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, further including: receiving a request for the expanded view dataset, responsive to the request, providing the expanded view dataset, by: retrieving, from a hardware storage device, the definition of the expanded view dataset, based on the definition of the expanded view dataset, retrieving, from one or more data sources, the base dataset and the one or more other datasets, and based on data in the retrieved datasets, generating the expanded view dataset (Reynolds [0125: “Also, a dataset attribute, datatype, a data classification, etc. may be derived based on, for example, data from user interface data 1292 (e.g., based on data representing an annotation entered via user interface 1202). As shown, collaborative dataset interface 1202 is configured to present a data preview 1204 of the set of data 1201a (or dataset thereof), with “???” indicating that a description or annotation is not included.”]; [See figure 12 and 0138: “According to some examples, a data preview of subsets of data may be presented in the user interface, the data preview showing portions of a dataset or set of data. A data preview may be generated (e.g., by a user interface element generator) to depict each subset of data as a column of data. In one example, a data view of a column of data may be presented with an unknown dataset attribute, whereby data may be received to annotate a column header to form an annotation to resolve the unknown dataset attribute. The annotation may refer to a datatype, a data classification, or the like.”]; [0125 and see figures 12 and 16]).
As per claim 12, rejection for claim 11 is incorporated and further Reynolds in view of Convertino discloses The method of claim 11, further including:
based on the expanded view dataset, determining whether to update a data catalog to specify the definition of the expanded view dataset as a data source, storing, in a hardware storage device, the definition of the expanded view dataset (Reynolds [0046: “As shown, dataset creation interface 102 includes a number of user interface elements to facilitate dataset creation, such as a search field 121, a dataset description field 103, a file upload interface 106, a create dataset activation input 141, and any other type of user interface element that may be used to create a dataset that, in turn, may be transformed into atomized datasets, such as atomized dataset 142a stored in repository 140.”]), and
registering the definition of the expanded view dataset with the data catalog [Convertino [0121-0122; 0144: “A Dataset is a class that abstracts a file, table, view, etc. of interest to a user. A DataElement is a class that abstracts a column of a dataset of interest to a user.”33]; [0061: “Knowledge base 130 also maintains relationships between data elements and data definitions which represent the semantics of the data element, e.g., where two particular datasets both contain the same specific type of data, or a column with the same set (or overlapping sets) of values (i.e., all the value can be checked against a common reference table).”]).
As per claim 13, rejection for claim 7 is incorporated and further Reynolds discloses The method of claim 7, further including:
based on the provided preview of the attributes of the expanded view dataset, determining whether to update the data catalog to specify the definition of the expanded view dataset as a data source (Reynolds [0049: “Therefore, user 108a may enter search terms into the search field 121 to search for any relevant datasets that may augment or otherwise supplement a current collaborative dataset.”]; [0130; 0138: “The correlated attributes, as generated by attribute correlator 1263, may facilitate the use of derived data or link-related data, as attributes, to form associate, combine, join, or merge datasets to form collaborative datasets.”] and in view of Convertino [0121-0122; 0144: “A Dataset is a class that abstracts a file, table, view, etc. of interest to a user. A DataElement is a class that abstracts a column of a dataset of interest to a user.”33]; [0061: “Knowledge base 130 also maintains relationships between data elements and data definitions which represent the semantics of the data element, e.g., where two particular datasets both contain the same specific type of data, or a column with the same set (or overlapping sets) of values (i.e., all the value can be checked against a common reference table).”]).
As per claim 14, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, wherein generating the available dataset includes:
using the definition of the expanded view dataset to only access those datasets with the specified one or more fields and including data of those accessed datasets into the available dataset (Reynolds [0045-0049: 0045: dataset creation and data interoperability, 0047: linking datasets, 0048: dataset attributes identified, 0049: access attributes.]).
As per claim 15, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, further including:
processing the generated available dataset to obtain a result from processing the data of the available dataset (Reynolds [0125, 0134, 0138-0139: “For example, input 1371 may be activated to add derived column 1392 to the dataset. Input 1373 may be activated to substitute and replace columns 1306a and 1306b with derived column 1392.”]).
As per claim 16, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, further including:
providing a user permission to access portions of the base dataset in the expanded view dataset, while denying a user access to remaining portions of the base dataset (Reynolds [0052: “User 108a may grant certain levels of access or permissions (e.g., “view only” permission, “view and edit” permission, etc.) In the event a certain dataset is protected, then user 108a may request access upon activation of input (“link”) 137 in dataset access request portion 138.”]).
As per claim 17, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, wherein the definition of the expanded view dataset comprises a computational graph that specifies a set of data processing operations to generate the expanded view dataset that includes the data from the base dataset and the other datasets related to the base dataset, the set of data processing operations including at least one operation to join the data from the base dataset and data from at least one of the other datasets related to the base dataset (Reynolds [0173; 0178: “For example, user interface elements may present information, (e.g., textually, statistically, graphically, etc.) that may convey characteristics of the data distribution and “shape,” among other things.”]; [0053: “In various examples, creation of a dataset may including forming links among atomized datasets, whereby at least some links can be formed via graph data (e.g., at levels at which graph data arrangements are stored in, for example, graph databases). According to some embodiments, graph data arrangements may facilitate connecting and relating increasing amounts of data relative to other data storage technologies that may be relatively inflexible in adapting to increased amounts of data (e.g., increases in relatively large amounts of data).”]; [0077: “Therefore, collaborative dataset consolidation system 410 need not be required to generate massive graphs based on numerous datasets, but rather, collaborative dataset consolidation system 410 may create a graph based on a collaborative dataset in one operational state (of a number of operational states), and can be partitioned in another operational state (but can be linked via links 411 to form the graph).”]).
As per claim 18, rejection for claim 1 is incorporated and further Reynolds discloses The method of claim 1, wherein the definition of the expanded view dataset provides logical access to data from the base dataset and the other datasets related to the base dataset (Reynolds [0172-0174: “FIG. 23 is an example of a data entry interface to access atomized datasets, according to some examples.”]).
As per claim 22, rejection for claim 21 is incorporated and further Reynolds discloses The method of claim 21, wherein the preview is generated at development time (Reynolds [0125: “As shown, collaborative dataset interface 1202 is configured to present a data preview 1204 of the set of data 1201a (or dataset thereof), with “???” indicating that a description or annotation is not included.” And 0049 discussing attribute expansion.]).
Claims 19-21 are rejected similarly with claim 1. Claim 19 is a system claim, claim 20 is a machine-readable hardware storage device, and claim 21 claims a method that includes metadata. Reynolds teaches a system with hardware storage device on paragraphs 0216-0217. Further metadata is taught on paragraph 0149. All claims are rejected similarly as claim 1.
Comments
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bar-Or et al. (US 20170286526) – Teaches generating previews of data and expanded views of datasets using definitions.
The examiner requests, in response to this Office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line no(s) in the specification and/or drawing figure(s). This will assist the examiner in prosecuting the application.
When responding to this office action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. He or she must also show how the amendments avoid such references or objections See 37 CFR 1.111(c).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to Taelor Kim whose telephone number is (571) 270-7166. The examiner can normally be reached on Monday-Thursday (11AM-5PM) EST.
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Taelor Kim
/TAELOR KIM/ Supervisory Patent Examiner, Art Unit 2836
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