SEMANTIC SEARCH TOOL FOR DOCUMENT TAGGING, INDEXING AND SEARCH

• US 20140040275A1
• Filed: 10/11/2013
• Published: 02/06/2014
• Est. Priority Date: 02/09/2010
• Status: Active Grant

• Current Assignee: Siemens AG
• Original Assignee: Siemens Corp. (Siemens AG)
• Inventors: Kalender, Murat, Toklu, Candemir, Hampel, Kenneth, Dang, JIangbo
• Granted Patent: US 9,684,683 B2
• Time in Patent Office: Days
• US Class Current: 707/741
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/31 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/3322 using system suggestions G06F16/3325 takes precedence
• CPC Class Codes: G06F 16/345 Summarisation for human users
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

A semantic tagging engine automatically generates semantic tags for the given documents and enables semantic search, based on meanings of search terms and content tags. A Semantic Knowledge Management Tool (SKMT) forms a semantic search and knowledge management platform to search, analyze and manage enterprise content. SKMT scans different content sources and generates indexes of semantic keywords. Its interface allows users to manage various data sources, search, explore and visualize search results at semantic level. SKMT provides high precision of semantic search and semantic data visualization.

Claims

1. A method for performing a semantic search to retrieve documents from a document repository, comprising:

a processor accepting through a graphical interface a search phrase provided by a user;

the processor analyzing the search phrase and suggesting a plurality of semantic search phrases generated from a stored vocabulary of an ontology to suggest a context;

the processor accepting a first semantic search phrase selected from the plurality of semantic search phrases;

the processor indexing and semantically tagging a plurality of documents in a storage medium, wherein at least one document was unstructured prior to the indexing and semantically tagging;

the processor extracting a plurality of semantic tags from the indexed and semantically tagged documents; and

the processor defining a plurality of groups based on the indexed and tagged documents.

2. The method of claim 1, wherein the at least one unstructured document is stored in a local file and is semantically indexed before the search phrase is accepted by the processor.

3. The method of claim 1, wherein the processor retrieves the at least one unstructured document via an Internet and semantically tags and indexes the retrieved document after the search phrase is accepted by the processor.

4. The method of claim 1, wherein the documents in the plurality of documents are indexed with unique identifications of semantic tags.

5. The method of claim 4, wherein the processor searches the indexed documents based on a unique identification of the first semantic search phrase.

6. The method of claim 1, wherein the semantically tagging enables a structured query search of the document that was unstructured.

7. The method of claim 1, wherein a group is determined by a keyword that occurs in a selected document in the storage medium.

8. The method of claim 1, wherein a group is determined by a semantic tag that occurs in a selected document in the storage medium.

9. The method of claim 8, wherein the group is represented in a semantic tag cloud.

10. The method of claim 1, further comprising:

selecting a group in the plurality of groups; and

updating the semantic search in accordance with the selected group.

11. A system to perform a semantic search to retrieve documents from a document repository, comprising:

a memory configured to store and retrieve data, including instructions;

a processor configured to execute instructions retrieved from the memory to perform the steps;

accepting a search phrase;

analyzing the search phrase and suggesting a plurality of semantic search phrases generated from a stored vocabulary of an ontology to suggest a context;

accepting a first semantic search phrase selected from the plurality of semantic search phrases;

storing in a storage medium at least one unstructured document;

indexing and semantically tagging a plurality of documents including the at least one unstructured document in the storage medium;

extracting a plurality of semantic tags from the indexed and semantically tagged documents; and

defining one or more groups based on the indexed and tagged documents.

12. The system of claim 11, wherein documents are stored in a local file and the documents are semantically indexed before the search phrase is accepted by the processor.

13. The system of claim 11, wherein the processor retrieves the at least one unstructured document via an Internet based on the search phrase and semantically tags and indexes the at least one unstructured document to make it a structured document.

14. The system of claim 11, wherein the documents in the plurality of documents are indexed with unique identifications of semantic tags.

15. The system of claim 14, wherein the processor searches the indexed documents based on a unique identification of the first semantic search phrase.

16. The system of claim 11, wherein the semantically tagging enables a structured query search of the at least one document that was previously unstructured.

17. The system of claim 11, wherein a group is determined by a keyword that occurs in a selected document in the storage medium.

18. The system of claim 11, wherein a group is determined by a semantic tag that occurs in a selected document in the storage medium.

19. The system of claim 18, wherein the group is represented in a semantic tag cloud.

20. The system of claim 11, further comprising the steps performed by the processor:

selecting a group in the plurality of groups; and

updating the semantic search in accordance with the selected group.