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 .
Claims 1, 9, & 17 are amended.
Claims 1-20 are pending.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because of the new grounds of rejection. See Office Action below.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 5-6, 9, 13, 15, & 17-20 is/are rejected under 35 U.S.C. 102(a)(1) as being unpatentable over DHEAP et al. (US Pub. No. 2011/0154239 A1).
In respect to Claim 1, DHEAP teaches:
a method comprising: receiving a first input identifying a dataset for ingestion into a data lake, the dataset including a plurality of attributes and interaction data obtained from an application, the interaction data indicating user interactions with a first attribute of the plurality of attributes; (DHEAP teaches [0006] the system performs “collecting, by a monitoring server, data regarding attributes of a user interacting with an application at a cline site, where the collected data has associated evaluation criteria; wherein this a direct structural match for receiving a dataset of attributes together with interaction data reflecting a user’s interactions with those attributes via an application.)
generating, based on the dataset and the interaction data, a first attribute consumption metric for the first attribute of the plurality of attributes of the dataset, wherein the first attribute consumption metric quantifies consumption for the first attribute based on a set of interactions with the first attribute by a set of users included in the interaction data and a set of weights associated with interactions of the set of interactions; (DHEAP teaches [Abstract, 0006, 0054] the evaluation criteria comprises a weighting schema, and each data element is assigned a default weighting, against which the given element is applied, directly quantifying the collected attribute-interaction data using per-interaction weights.)
causing a dashboard to present a representation of the plurality of attributes in the dataset; (DHEAP teaches [0006] the collected, weighted attribute data is collectively represented via a display, described elsewhere as being shown [0054] via a heat map which is a dashboard style representation of the attribute data.)
obtaining a second input to the dashboard associated with the first attribute; (DHEAP teaches [0006] the system provides a mechanism for dynamically adjusting said evaluation criteria assigned to selected data attributes, wherein said mechanism may be dynamically modified; implemented via [0033] adjusting a filter value of the evaluation criteria via a direct user manipulation of an adjustable control; e.g. a Customer Loyalty slider; tied to a specific data attribute; wherein this a direct match for a second, attribute-associated input to the displayed dashboard.)
and causing, in response to the second input, at least one attribute depicted in the representation of the plurality of attributes to be modified by at least displaying a visual representation of the first attribute consumption metric (DHEAP teaches [0006, 0033] applying an adjusted evaluation criteria to collected data; and collectively representing the data evaluated according to adjusted criteria via display – i.e., in direct response to the second (slider/control) input, the displayed representation is recomputed and redisplayed using the updated weighting, which matches the modify-and-redisplay sequence.)
As per Claim 2, DHEAP teaches:
wherein a first weight of the set of weights corresponds to a recency of an interaction with the dataset by a first user of the set of users such that the first weight causes more recent interactions set of interactions to have a higher value relative to other interactions set of interactions (DHEAP teaches [0052] attributes may include a moving time window reflecting what particular actions or events had taken place during a given time interval; wherein this represents a recency windowing mechanic.)
As per Claim 5, DHEAP teaches:
generating, in response to the second input, a filtered dataset comprising the first attribute (DHEAP teaches [0006] the system provides a mechanism for dynamically adjusting said evaluation criteria assigned to selected data attributes, wherein said mechanism may be dynamically modified; implemented via [0033] adjusting a filter value of the evaluation criteria via a direct user manipulation of an adjustable control; e.g. a Customer Loyalty slider; tied to a specific data attribute; wherein this a direct match for a second, attribute-associated input to the displayed dashboard.)
As per Claim 6, DHEAP teaches:
wherein the first attribute consumption metric quantifies a subset of interactions of the set of interactions by a subset of users of the set of users to filter the dataset based on the first attribute (DHEAP teaches [0006, 0033] the system filters based on a minimum number of past purchases, where adjusting a higher slider setting causes data from more loyal customers to be displayed, i.e., a subset of interactions (purchases) by a subset of users (loyal customers) is what quantifies the metric driving the attribute-based filter.)
Claims 9 & 13 is the non-transitory media claim corresponding to method claims 1 & 6 respectively, therefore is rejected for the same reasons noted previously.
As per Claim 15, DHEAP teaches:
wherein a weight value of the set of weight values includes at least one of: a recency of an interaction, a role associated with a user, and an experience level associated with a user (DHEAP teaches [0052] attributes may include a moving time window reflecting what particular actions or events had taken place during a given time interval; wherein this represents a recency windowing mechanic.)
Claim 17 is the system claim corresponding to method claim 1 above, therefore is rejected for the same reasons noted previously.
As per Claim 18, DHEAP teaches:
wherein the attribute consumption metric quantifies at least one of: filtering the dataset based on the attribute, selecting data of the dataset based on the attribute, segmenting the dataset based on the attribute, and generating a visualization of the dataset based on the attribute (DHEAP teaches [0006, 0033] the system filters based on a minimum number of past purchases, where adjusting a higher slider setting causes data from more loyal customers to be displayed, i.e., a subset of interactions (purchases) by a subset of users (loyal customers) is what quantifies the metric driving the attribute-based filter.)
Claim 19 is the system claim corresponding to media claim 15 above, therefore is rejected for the same reasons noted previously.
As per Claim 20, DHEAP teaches:
wherein the visual representation of the attribute consumption metric indicates a value associated with the attribute based on a subset of interactions of the set of interactions and a subset of weights of the set of weights (DHEAP teaches [Abstract] collectively representing the data evaluated according to the adjusted criteria via the display mechanism.)
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over DHEAP in view of Schneider (US Pub. No. 2013/0031015 A1).
As per Claim 3, Schneider teaches:
wherein a first weight of the set of weights corresponds to a role associated with a first user of the set of users such that the first weight causes the role to have a higher value relative to other roles (Schneider teaches [0116] the system allows different weighting for the skills mapped to job profile and use this weighting while calculating skill score – i.e., the weight applied to a given interaction and skill varies by the job profile role associated with it.)
It would have been obvious to one of ordinary skill in the art at the time of the filing date of the invention to incorporate the teachings of Schneider into the system of DHEAP. One of ordinary skill in the art would be motivated to provide a system for attribute scoring for personal tracking and development scoring that determines an individual’s proficiency for skills that are mapped to a job profile. (Schneider [0002])
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over DHEAP in view of Ipeirotis et al. (US Pub. No. 2015/0242447 A1).
As per Claim 4, Ipeirotis teaches:
wherein a first weight of the set of weights corresponds to an experience level associated with a first user of the set of users such that the first weight causes an experience level to have a higher value relative to experience levels (Ipeirotis teaches [0005] the system computes an expertise confidence score for a new contribution based on a comparison of the new contribution with previously correct and incorrect contributions – the contributor’s own track record (a functional proxy for experience) directly weights how much a given contribution/interaction counts.)
It would have been obvious to one of ordinary skill in the art at the time of the filing date of the invention to incorporate the teachings of Ipeirotis into the system of DHEAP. One of ordinary skill in the art would have been motivated to provide a contribution confidence score based on a combination of the first expertise confidence score and the second expertise confidence score and automatically adding the new contribution to active contributions. (Ipeirotis [0009])
Claim(s) 7 & 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over DHEAP in view of Hanrahan et al. (US Pub. No. 2006/0206512 A1).
As per Claim 7, Hanrahan teaches:
wherein the first attribute consumption metric quantifies a subset of interactions of the set of interactions by a subset of users of the set of users to encode a visualization of the dataset using the first attribute (Hanrahan teaches [0059, 0095, 0158] a user drags dimension levels or measures to shelves to define the graphic, where the field on a given shelf directly determines color, size, or position of the resulting marks, which is the foundational mechanism by which an attribute is used to encode a visualization.)
It would have been obvious to one of ordinary skill in the art at the time of the filing date of the invention to incorporate the teachings of Hanrahan into the system of DHEAP. One of ordinary skill in the art would be motivated to provide a system for visualizing data such as database information and a system for determining an appropriate mark based on types of data being visualized. (Hanrahan [0001])
Claim 14 is the media claim corresponding to method claim 7 above, therefore is rejected for the same reasons noted previously.
Claim(s) 8 & 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over DHEAP in view of Sugnet et al. (US Patent No. 9,299,091 B1).
As per Claim 8, Sugnet teaches:
wherein the first attribute consumption metric quantifies a subset of interactions of the set of interactions by a subset of users of the set of users used to generate a segmentation rule of a marketing campaign (Sugnet teaches [column 9, lines 4-11] an audience segment can be selected with the additional constraint that tracked entities in the audience segment are associated with specific attribute values, located [column 4, lines 49-67] by querying the data repository for a specific set of attribute values; wherein this constitutes the underlying mechanism of using an attribute’s values to define a segment.)
It would have been obvious to one of ordinary skill in the art at the time of the filing date of the invention to incorporate the teachings of Sugnet into the system of DHEAP. One of ordinary skill in the art would be motivated to provide a system for selecting an audience segment based on its aggregate similarity to a known audience. (Sugnet [column 1, lines 33-35])
Claim 16 is the media claim corresponding to the method claim 8 above, therefore is rejected for the same reasons noted previously.
Claim(s) 10 & 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over DHEAP in view of Auerbach et al. (US Pub. No. 2007/0027843 A1).
As per Claim 10 Auerbach teaches:
wherein ingesting into the data lake the dataset further comprising ingesting sample data from the dataset into a landing zone separate from the data lake (Auerbach teaches [0004] incoming application data is split onto two parallel paths – dividing received application data into an aggregate data store and one or more raw data stores; where the aggregate store receives the fully processed data while the system separately samples the received data and stores the sample portions of the received data in a raw data store, a distinct store on [0033, 0035] distinct higher speed media.)
It would have been obvious to one of ordinary skill in the art at the time of the filing date of the invention to incorporate the teachings of Auerbach into the system of DHEAP. One of ordinary skill in the art would have been motivated to provide a reporting tool that is able to locate the correct data store to respond to queries, extract the data, and generate a report. (Auerbach [0004])
As per Claim 12, Auerbach teaches:
wherein the portion of the dataset further comprises a stream of the sample data being ingested into in the landing zone separate from the data lake (Auerbach teaches [Abstract, 0004, 0031] sampling the received raw data at a first sampling rate when a rate of incoming raw data exceeds a threshold leve, with the sampling rate itself varying based on the [0031] rate of incoming raw data – and [Claim 1] continuously storing a sampled data portion in a first memory medium as that stream arrives, distinct from the aggregate store.)
It would have been obvious to one of ordinary skill in the art at the time of the filing date of the invention to incorporate the teachings of Auerbach into the system of DHEAP. One of ordinary skill in the art would have been motivated to provide a reporting tool that is able to locate the correct data store to respond to queries, extract the data, and generate a report. (Auerbach [0004])
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over DHEAP & Auerbach, and further in view of Daly et al. (US Patent No. 9,600,776 B1).
As per Claim 11, Daly teaches:
wherein the portion of the dataset further comprises the sample data stored in the landing zone separate from the data lake (Daly teaches [column 4, lines 24-39] the system maintains data reservoirs of previously assessed data samples, decides [column 2, lines 34-61] whether the new data sample statistically belongs in the reservoir before adding it (i.e., the reservoir holds a curated subset, not the full incoming data), and [column 1, lines 60-67] calculates an overall data quality estimate for the reservoir using data quality estimates…associated with each of the data samples”, wherein this is a metric computed directly from the segregated, stored sample set.)
It would have been obvious to one of ordinary skill in the art at the time of the filing date of the invention to incorporate the teachings of Daly into the systems of DHEAP & Auerbach. One of ordinary skill in the art would be motivated to provide a system for updating summary statistics in an instance in which the new data sample is added while comparing summary statistics to training data, wherein a predictive model is adapted using the training data samples. (Daly [column 2, lines 36-44])
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Conclusion
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/JOSHUA BULLOCK/Primary Examiner, Art Unit 2153 September 9, 2026
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