Semantics for document-oriented databases

1. A method, the method comprising:

receiving a set of documents, the set including instances of unstructured or semi-structured documents, the unstructured or semi-structured documents being data encoded to include at least two different data-types;

parsing the set of documents to obtain metadata information regarding each of the documents in the set of documents;

automatically determining data-types for each document in the set of documents based on the metadata information regarding each of the documents in the set of documents obtained by the parsing;

generating a hierarchical semantic representation of the set of documents based on the determined data-types for each of the documents in the set of documents, the hierarchical semantic representation of the set of documents including a value for a merged weight and a merged data type rank that is calculated based on a weight and a data type rank calculated for each of the documents in the set of documents;

storing the hierarchical semantic representation of the set of documents; and

querying, by a semantic layer of an application that processes structured hierarchical data, the stored hierarchical semantic representation of the set of unstructured or semi-structured documents encoded to include the at least two data-types.

2. The method of claim 1 , wherein the parsing of the set of documents includes parsing a subset of the set of documents.

3. The method of claim 1 , wherein the parsing comprises parsing individual documents in the set of documents to obtain information regarding the individual documents in the set of documents.

4. The method of claim 3 , further comprising:

merging the determined data-types for the individual documents; and

generating the hierarchical semantic representation for the set of documents based on the merged determined data-types for the individual documents.

5. The method of claim 1 , wherein the information obtained by parsing the set of documents comprises key-value pairs and the values may be represented by a combination of at least one of a number, a string, a Boolean value, an array, an unordered associative array, and a null value without limit.

6. The method of claim 1 , wherein the instances of the unstructured or semi-structured documents does not adhere to a predefined set of semantics.

7. The method of claim 1 , wherein the instances of the unstructured or semi-structured documents is retrieved from a document-oriented database.

8. The method of claim 1 , wherein the information obtained by parsing the set of documents corresponds to an internal structure of the unstructured or semi-structured documents, including at least a data-type for key-value pairs of each of the unstructured or semi-structured documents.

9. A non-transitory computer-readable medium having:

instructions to receive a set of documents, the set including instances of an unstructured document or semi-structured documents, the unstructured or semi-structured documents being data encoded to include at least two different data-type;

instructions to parse the set of documents to obtain metadata information regarding each of the documents in the set of documents;

instructions to automatically determine data-types for each document in the set of documents based on the metadata information regarding each of the documents in the set of documents obtained by the parsing;

instructions to generate a hierarchical semantic representation of the set of documents based on the determined data-types for each of the document in the set of documents, the hierarchical semantic representation of the set of documents including a value for a merged weight and a merged data type rank that is calculated based on a weight and a data type rank calculated for each of the documents in the set of documents;

instructions to store the hierarchical semantic representation of the set of documents; and

instructions to query, by a semantic layer of an application that processes structured hierarchical data, the stored hierarchical semantic representation of the set of unstructured or semi-structured documents encoded to include the at least two data-types.

10. The medium of claim 9 , wherein the parsing of the set of documents includes parsing a subset of the set of documents.

11. The medium of claim 9 , wherein the information obtained by parsing the set of documents is represented as metadata.

12. The medium of claim 9 , wherein the parsing comprises parsing individual documents in the set of documents to obtain information regarding the individual documents in the set of documents.

13. The medium of claim 12 , further comprising:

instructions to merge the determined data-types for the individual documents; and

instructions to generate the hierarchical semantic representation for the set of documents based on the merged determined data-types for the individual documents.

14. The medium of claim 9 , wherein the information obtained by parsing the set of documents comprises key-value pairs and the values may be represented by a combination of at least one of a number, a string, a Boolean value, an array, an unordered associative array, and a null value without limit.

15. The medium of claim 9 , wherein the instances of the unstructured or semi-structured documents does not adhere to a predefined set of semantics.

16. The medium of claim 9 , wherein the instances of the unstructured or semi-structured documents is retrieved from a document-oriented database.

17. The medium of claim 9 , wherein the information obtained by parsing the set of documents corresponds to an internal structure of the unstructured or semi-structured documents, including at least a data-type for key-value pairs of each of the unstructured or semi-structured documents.

18. A system comprising:

a database; and

a sever including a processor and a driver, the driver configured to make calls to the database and in cooperation with the processor to:

receive a set of documents, the set including instances of unstructured or semi-structured documents, the unstructured or semi-structured documents being data encoded to include at least two different data-type;

parse the set of documents to obtain metadata information regarding each of the documents in the set of documents;

automatically determine data-types for each document in the set of documents based on the metadata information regarding each of the documents in the set of documents obtained by the parsing;

generate a hierarchical semantic representation of the set of documents based on the determined data-types for each of the document in the set of documents, the hierarchical semantic representation of the set of documents including a value for a merged weight and a merged data type rank that is calculated based on a weight and a data type rank calculated for each of the documents in the set of documents;

store the hierarchical semantic representation of the set of documents; and

query, by a semantic layer of an application that processes structured hierarchical data the stored hierarchical semantic representation of the set of unstructured or semi-structured documents encoded to include the at least two data-types.

19. The system of claim 18 , wherein the parsing of the set of documents includes parsing a subset of the set of documents.