APPARATUS AND METHODS FOR DETERMINING A HIERARCHICAL LISTING OF INFORMATION GAPS
An apparatus for determining a hierarchical listing of information gaps for a user is provided. The apparatus includes a processor and a memory connected to the processor. The memory contains instructions configuring the processor to receive an instance of an identification datum from a user device, where the identification datum describes an output type from the user device at a time, receive a target status datum from a database connected to the processor, where the target status datum describes an optimal output type between a minimal output type and a maximum output type, and to classify the identification datum and the target status datum to categories representing identification data. The processor may identify an instance of a gap between identification data and display an input field to the user capable of displaying a hierarchical listing of information gaps based on a user-input datum.
1 . An apparatus for determining a hierarchical listing of information gaps, the apparatus comprising:
a processor; and
a memory connected to the processor, the memory containing instructions configuring the processor to:
receive a first identification datum from a user device at a first time;
receive a target status datum from a database connected to the processor;
classify, using a machine learning model, the first identification datum to an outlier cluster;
identify a first gap datum between the target status datum and the first identification datum;
receive an updated identification datum from the user device at a second time;
identify a second gap datum between the target status datum and the updated identification datum;
generate an updated hierarchical listing based at least on the second gap datum and the outlier cluster;
generate an interface query data structure including an input field, wherein the interface query data structure configures a remote display device to:
receive the updated identification datum using the input field; and
display the updated hierarchical listing.
2 . The apparatus of claim 1 , wherein receiving the target status datum further comprises:
scoring, using the machine learning model, the hierarchical listing of information gaps by applying an algorithmic model built from a historical dataset, wherein:
algorithmic model is applied to a new dataset and is configured to track trends associated with at least the updated identification datum; and
the hierarchical listing is configured to be scored between a minimum value and a maximum value.
3 . The apparatus of claim 2 , wherein the interface query data structure further configures the remote display device to display an information gap assessment area, wherein the information gap assessment area comprises a human-interactive portion comprising a query for a human to provide feedback on a form of input.
4 . The apparatus of claim 3 , wherein the memory contains instructions further configuring the processor to:
receive the feedback through the human-interactive portion of the information gap assessment area; and
refine the machine learning model using the feedback.
5 . The apparatus of claim 1 , wherein the first identification datum is received from one or more web trackers configured to track activity of a user on the internet.
6 . The apparatus of claim 1 , wherein the first identification datum is received from one or more data scrapers.
7 . The apparatus of claim 6 , wherein the one or more data scrapers are configured to gather data from one or more of a user's social media profiles.
8 . The apparatus of claim 1 , wherein generating the interface query data structure further comprises:
retrieving data describing attributes of a user from a database communicatively connected to the processor; and
generating the interface query data structure based on the data describing attributes of the user, wherein generating the interface query data structure further comprises:
determining a norm from the first gap datum to the second gap datum; and
configuring the remote display device to display a representation of the norm.
9 . The apparatus of claim 1 , wherein the remote display device comprises a smartphone.
10 . The apparatus of claim 1 , wherein the first identification datum comprises a type indicator value.
11 . A method for determining a hierarchical listing of information gaps, the method comprising:
receiving, by a processor, a first identification datum from a user device at a first time;
receiving, by the processor, a target status datum from a database connected to the processor;
classifying, by the processor using a machine learning model, the first identification datum to an outlier cluster;
identifying, by the processor, a first gap datum between the target status datum and the first identification datum;
receiving, by the processor, an updated identification datum from the user device at a second time;
identifying, by the processor, a second gap datum between the target status datum and the updated identification datum;
generating, by the processor, an updated hierarchical listing based at least on the second gap datum and the outlier cluster;
generate, by the processor, an interface query data structure including an input field wherein the interface query data structure configures a remote display device to:
display an input field;
receive the updated identification datum a user-input datum using the input field, wherein the user-input datum describes data for updating the first identification datum; and
display a user activity level summary based on the user-input datum the updated hierarchical listing.
12 . The method of claim 11 , wherein receiving the target status datum further comprises:
scoring, using the machine learning model, the hierarchical listing of information gaps by applying an algorithmic model built from a historical dataset, wherein:
algorithmic model is applied to a new dataset and is configured to track trends associated with at least the updated identification datum; and
the hierarchical listing is configured to be scored between a minimum value and a maximum value.
13 . The method of claim 12 , wherein the interface query data structure further configures the remote display device to display an information gap assessment area, wherein the information gap assessment area comprises a human-interactive portion comprising a query for a human to provide feedback on a form of input.
14 . The method of claim 13 , further comprising:
receiving, by the processor, the feedback through the human-interactive portion of the information gap assessment area; and
refining, by the processor, the machine learning model using the feedback.
15 . The method of claim 11 , wherein the first identification datum is received from one or more web trackers configured to track activity of a user on the internet.
16 . The method of claim 11 , wherein the first identification datum is received from one or more data scrapers.
17 . The method of claim 16 , wherein the one or more data scrapers are configured to gather data from one or more of a user's social media profiles.
18 . The method of claim 11 , wherein generating the interface query data structure further comprises:
retrieving data describing attributes of a user from a database communicatively connected to the processor; and
generating the interface query data structure based on the data describing attributes of the user, wherein generating the interface query data structure further comprises:
determining a norm from the first gap datum to the second gap datum; and
configuring the remote display device to display a representation of the norm.
19 . The method of claim 11 , wherein the remote display device comprises a smartphone.
20 . The method of claim 11 , wherein the first identification datum comprises a type indicator value.