INPUT/OUTPUT INTERFACE FOR CONTEXTUAL ANALYSIS ENGINE

• US 20150106156A1
• Filed: 10/15/2013
• Published: 04/16/2015
• Est. Priority Date: 10/15/2013
• Status: Active Grant

• Current Assignee: Adobe Inc.
• Original Assignee: Adobe Systems Incorporated (Adobe Inc.)
• Inventors: Chang, Walter, Sadler, Shone, Jared, David, Chen, Chris
• Granted Patent: US 10,430,806 B2
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A contextual analysis engine systematically extracts, analyzes and organizes digital content stored in an electronic file such as a webpage. Content can be extracted using a text extraction module which is capable of separating the content which is to be analyzed from less meaningful content such as format specifications and programming scripts. The resulting unstructured corpus of plain text can then be passed to a text analytics module capable of generating a structured categorization of topics included within the content. This structured categorization can be organized based on a content topic ontology which may have been previously defined or which may be developed in real-time. The systems disclosed herein optionally include an input/output interface capable of managing workflows of the text extraction module and the text analytics module, administering a cache of previously generated results, and interfacing with other applications that leverage the disclosed contextual analysis services.

Claims

1. A method of analyzing digital content to generate contextual analysis data based on the digital content, the method comprising:

receiving a request to analyze the digital content;

invoking a text extraction service configured to extract a corpus of plain text from the digital content;

receiving, from a text analytics service, topic data derived from the corpus of plain text, the topic data including a listing of topics and corresponding relevancy scores for the listed topics; and

generating a hierarchical output schema that includes a plurality of resource nodes, wherein a first resource node contains at least a portion of the corpus of plain text, and wherein a second resource node contains topics included within the listing received from the text analytics service.

2. The method of claim 1, wherein the digital content comprises a webpage containing JavaScript elements.

3. The method of claim 1, wherein the request to analyze the digital content complies with a representational state transfer (REST) architecture.

4. The method of claim 1, wherein the request to analyze the digital content complies with an application programming interface mechanism.

5. The method of claim 1, wherein:

the digital content comprises a webpage containing JavaScript elements; and

the text extraction service uses a headless browser to extract the corpus of plain text.

6. The method of claim 1, wherein:

the request to analyze the digital content includes a text extraction parameter; and

invoking the text extraction service comprises passing the text extraction parameter to a text extraction module.

7. The method of claim 1, wherein the topic data received from the text analytics service further comprises frequency counts for the listed topics.

8. A method of managing requests to obtain contextual analysis data, the method comprising:

receiving, from a content administration client, a request for contextual analysis data based on digital content that is identified in the request;

determining whether the requested contextual analysis data is stored in a results cache;

where it is determined that the requested contextual analysis data is stored in the results cache, providing the requested contextual analysis data to the content administration client; and

where a determination is made that the requested contextual analysis data is not stored in the results cache,

using a headless browser to extract a corpus of plain text from the digital content,

generating new contextual analysis data that includes at least a portion of the corpus of plain text and a hierarchal listing of topics extracted from the corpus of plain text,

persisting the new contextual analysis data in the results cache, and

providing the new contextual analysis data to the content administration client.

9. The method of claim 8, wherein the headless browser is provided by a plugin that is scriptable with a JavaScript application programming interface (API).

10. The method of claim 8, wherein determining whether the requested contextual analysis data is stored in the results cache comprises comparing a last-modified timestamp associated with the digital content with a timestamp for contextual analysis data stored in the results cache.

11. The method of claim 8, wherein determining whether the requested contextual analysis data is stored in the results cache comprises comparing a hash derived from the digital content with a hash derived from digital content used to generate contextual analysis data stored in the results cache.

12. The method of claim 8, wherein the digital content is identified in the request using a uniform resource locator (URL).

13. A system for obtaining contextual analysis data corresponding to a webpage, the system comprising:

a results cache having persisted therein contextual analysis data;

an input interface configured to receive, from a content administration tool, a request to obtain contextual analysis data corresponding to a webpage;

a cache manager configured to determine whether the results cache has persisted therein the contextual analysis data corresponding to the webpage;

an orchestration manager configured to invoke a text extraction service so as to extract a corpus of plain text from the webpage using a headless browser; and

an output interface configured to provide, to the content administration tool, the contextual analysis data corresponding to the webpage, wherein the contextual analysis data provided to the content administration tool is either (a) obtained from the cache manager or (b) derived from the corpus of plain text that is extracted from the webpage.

14. The system of claim 13, wherein the output interface further comprises a reporting and visualization module configured to format the contextual analysis data according to a hierarchical output schema that is defined in an output format repository.

15. The system of claim 13, wherein the orchestration manager is further configured to invoke a text analytics service that is configured to produce a listing of topics contained within the corpus of plain text.

16. The system of claim 13, wherein the input interface includes an input application programming interface (API) configured to receive requests that are compliant with both a hypertext markup language (HTML) and a representation state transfer (REST) architecture.

17. The system of claim 13, wherein the request specifies an endpoint that specifies a network address indicating where the text extraction service can be accessed.

18. A non-transient computer readable medium having instructions encoded thereon that, when executed by one or more processors, causes a digital content analysis process to be carried out, the process comprising:

receiving a request to analyze the digital content;

invoking a text extraction service configured to extract a corpus of plain text from the digital content;

receiving, from a text analytics service, topic data derived from the corpus of plain text, the topic data including a listing of topics and corresponding relevancy scores for the listed topics; and

generating a hierarchical output schema that includes a plurality of nodes, wherein a first node contains at least a portion of the corpus of plain text, and wherein a second node contains topics included within the listing received from the text analytics service.

19. The non-transient computer readable medium of claim 18, wherein the hierarchical output schema further comprises an @context section that specifies a topic domain ontology that is used to generate the listing of topics.

20. The non-transient computer readable medium of claim 18, wherein the first and second nodes are resource nodes.

21. The non-transient computer readable medium of claim 18, wherein:

the process further comprises receiving, from a second text analytics service, statistical data derived from the corpus of plain text; and

the hierarchical output schema further comprises a third node containing at least a portion of the statistical data.

22. The non-transient computer readable medium of claim 18, wherein the text analytics service uses a headless browser to extract the corpus of plain text.