System and method for automatic content aggregation database evaluation

• US 10,459,956 B1
• Filed: 12/14/2016
• Issued: 10/29/2019
• Est. Priority Date: 04/08/2016
• Status: Active Grant

• Current Assignee: Pearson Education Incorporated (Pearson plc)
• Original Assignee: Pearson Education Incorporated (Pearson plc)
• Inventors: York, Sean, Stewart, Tim, Strong, David, Hellman, Scott, Murray, William
• Primary Examiner(s): Mackes, Kris E
• Application Number:
  US15/379,403
• Time in Patent Office: 1,049 Days
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/322 Trees
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/338 Presentation of query results
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 40/123 Storage facilities
• CPC Class Codes: G06F 40/131 Fragmentation of text files, e.g. creating reusable text-blocks; Linking to fragments, e.g. using XInclude; Namespaces
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G06F 40/216 using statistical methods
• CPC Class Codes: G06F 40/226 Validation
• CPC Class Codes: G06F 40/289 Phrasal analysis, e.g. finite state techniques or chunking
• CPC Class Codes: G06F 40/35 Discourse or dialogue representation
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/02 Neural networks
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 : Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 : Inference or reasoning models
• CPC Class Codes: G06N 7/01 : Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 30/02 : Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0224 : based on user history
• CPC Class Codes: G06Q 30/0269 : based on user profile or attribute
• CPC Class Codes: G06Q 50/20 : Education
• CPC Class Codes: G09B 5/00 : Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F
• CPC Class Codes: G09B 7/02 : of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
• CPC Class Codes: H04L 12/407 : with decentralised control
• CPC Class Codes: H04L 12/4641 : Virtual LANs, VLANs, e.g. virtual private networks [VPN] LAN interconnection over a bridge based backbone H04L12/462; encapsulation techniques H04L12/4633; routing of packets H04L45/00; packet switches H04L49/00; virtual private networks for security H04L63/0272
• CPC Class Codes: H04L 41/0806 : for initial configuration or provisioning, e.g. plug-and-play
• CPC Class Codes: H04L 41/142 : using statistical or mathematical methods
• CPC Class Codes: H04L 41/145 : involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 41/5051 : Service on demand, e.g. definition and deployment of services in real time
• CPC Class Codes: H04L 43/16 : Threshold monitoring
• CPC Class Codes: H04L 45/74591 : using content-addressable memories [CAM]
• CPC Class Codes: H04L 47/10 : Flow control; Congestion control
• CPC Class Codes: H04L 65/1069 : Session establishment or de-establishment
• CPC Class Codes: H04L 67/02 : based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/06 : specially adapted for file transfer, e.g. file transfer protocol [FTP]
• CPC Class Codes: H04L 67/10 : in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/1095 : Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
• CPC Class Codes: H04L 67/1097 : for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
• CPC Class Codes: H04L 67/146 : Markers for unambiguous identification of a particular session, e.g. session cookie or URL-encoding
• CPC Class Codes: H04L 67/306 : User profiles
• CPC Class Codes: H04L 67/52 : specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/567 : Integrating service provisioning from a plurality of service providers
• CPC Class Codes: H04L 67/61 : taking into account QoS or priority requirements
• CPC Class Codes: H04W 88/02 : Terminal devices

Abstract

Systems and methods for content aggregation creation are disclosed herein. The system can include memory having a content database and an aggregation database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include a server that can: provide content to the user device via a first electrical signal; receive a selection of a portion of the provided content from the user device via a second electrical signal; automatically extract sentences from the selected portion of the provided content via a natural language processor; automatically generate a parse tree for one of the automatically extracted sentences; identify noun phrases from the part of speech tags within the parse tree; place content associated with one of the noun phrase in a content aggregation; and output the content aggregation to the user device.

Claims

1. A system for evaluation of a group of digital flash cards comprising:

memory comprising;

a content library database, wherein the content library database is configured to store a plurality of digital flash cards;

a user device comprising;

a first network interface configured to exchange data via a communication network; and

a first I/O subsystem configured to convert electrical signals to user interpretable outputs via a user interface; and

one or more servers, wherein the one or more servers are configured to;

receive a user identifier from the user device after authentication;

identify a user associated with the received user identifier;

receive an evaluation request from the user, wherein the evaluation request defines a set of digital flash cards associated in the content library database with the user identifier;

retrieve the set of digital flash cards associated with the user identifier, and having been selected by a flash card content author for inclusion within a group of flash cards;

retrieve a syllabus data relevant to the defined set of digital flash cards, and associated in the content library database with the user identifier, and with a class, group, assignment, or assessment, wherein the syllabus data identifies a plurality of topics, and wherein at least a subset of the set of digital flash cards are linked together by a common topic in the plurality of topics;

compare the retrieved set of digital flash cards to the retrieved syllabus data;

identify a flash card gap, wherein identifying the flash card gap comprises identifying, within the plurality of topics in the retrieved syllabus data, at least one digital flash card in the set of digital flash cards having no corresponding content associated with at least one topic in the plurality of topics; and

generate and send an alert to a user device identifying the flash card gap.

2. The system of claim 1, wherein the set of digital flash cards comprise some of the plurality of digital flash cards stored in the content library database.

3. The system of claim 2, wherein the set of digital flash cards are linked by a common attribute.

4. The system of claim 3, wherein the common attribute comprises at least one of:

creation by a user;

or selection by the user.

5. The system of claim 4, wherein the user has a first access level to digital flash cards created by the user and a second access level to digital flash cards selected by the user.

6. The system of claim 1, wherein the one or more servers are further configured to resolve the identified flash card gaps.

7. The system of claim 6, wherein resolving the identified flash card gaps comprises identifying at least one potential gap resolution.

8. The system of claim 7, wherein identifying at least one potential gap resolution comprises searching the content library database for at least one digital flash card to resolve the identified flash card gap.

9. The system of claim 7, wherein identifying at least one potential gap resolution comprises identifying at least one data packet for providing to the user in connection with prompting the user to generate additional digital flash cards.

10. The system of claim 7, wherein the alert comprises code to direct the user device to provide an indicator of the received alert.

11. The system of claim 10, wherein the indicator of the alert comprises at least one of:

an aural indicator;

a tactile indicator;

or visual indicator.

12. A method for evaluation of a group of digital flash cards comprising:

receiving a user identifier from a user device at one or more servers after authentication;

identifying a user associated with the received user identifier with the one or more servers;

receiving an evaluation request from the user, wherein the evaluation request defines a set of digital flash cards associated in the content library database with the user identifier;

retrieving the set of digital flash cards associated with the user identifier, and having been selected by a flash card content author for inclusion within a group of flash cards;

retrieving syllabus data relevant to the defined set of digital flash cards, and associated in the content library database with the user identifier, and with a class, group, assignment, or assessment, wherein the syllabus data identifies a plurality of topics, and wherein at least a subset of the set of digital flash cards are linked together by a common topic in the plurality of topics;

comparing the retrieved set of digital flash cards to the retrieved syllabus data;

identify a flash card gap, wherein identifying a flash card gap comprises identifying, within the plurality of topics in the retrieved syllabus data, at least one digital flash card in the set of digital flash cards having no corresponding content associated with at least one topic in the plurality of topics; and

generating and sending an alert to the user device identifying the flash card gap.

13. The method of claim 12, wherein the set of digital flash cards comprise some of a plurality of digital flash cards stored in a content library database.

14. The method of claim 13, wherein the set of digital flash cards are linked by a common attribute, wherein the common attribute comprises at least one of:

creation by a user;

or selection by the user.

15. The method of claim 14, wherein the user has a first access level to digital flash cards created by the user and a second access level to digital flash cards selected by the user.

16. The method of claim 12, further comprising resolving the identified flash card gaps, wherein resolving the identified flash card gaps comprises identifying at least one potential gap resolution.

17. The method of claim 16, wherein identifying at least one potential gap resolution comprises searching a content library database for at least one digital flash card to resolve the identified flash card gap.

18. The method of claim 16, wherein identifying at least on potential gap resolution comprises identifying at least one data packet for providing to the user in connection with prompting the user to generate additional digital flash cards.

19. The method of claim 18, wherein the alert comprises code to direct the user device to provide an indicator of the received alert.

20. The method of claim 19, wherein the indicator of the alert comprises at least one of:

an aural indicator;

a tactile indicator;

or visual indicator.