SYSTEM AND METHOD FOR DETERMINATION OF CAUSALITY BASED ON BIG DATA ANALYSIS

1 . A method for determining causality based on big data analysis, comprising:

extracting a plurality of unstructured data elements from a plurality of unstructured big data sources;

generating at least one signature for each of the plurality of unstructured data elements;

identifying at least one common pattern within the signatures of the plurality of unstructured data elements;

matching the at least one common pattern to at least one hypothesis by comparing at least one signature of the common pattern to at least one hypothesis; and

determining the causality of the at least one common pattern based on the at least one hypothesis matching the at least one common pattern.

2 . The method of claim 1 , further comprising:

generating the at least one signature for the at least one hypothesis.

3 . The method of claim 1 , wherein identifying the at least one common pattern further comprises:

clustering the signatures identified to have common patterns; and

correlating the generated clusters to identify associations between their respective identified common patterns.

4 . The method of claim 1 , wherein determining the causality further comprises:

correlating the at least one hypothesis matching the at least one common pattern.

5 . The method of claim 1 , wherein determining the causality further comprises:

computing a matching score based on the comparisons of the signatures;

determining a hypothesis having the highest matching score to be the causality.

6 . The method of claim 1 , wherein the at least one hypothesis is textual content representing a series of natural events, wherein the at least one hypothesis is extracted from big data sources.

7 . The method of claim 1 , wherein the unstructured data element is at least one of: multimedia content, a document, metadata, a collection of health records, analog data, a file, unstructured text, and a web page.

8 . The method of claim 7 , wherein the multimedia content element is at least one of: an image, graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, images of signals, combinations thereof, and portions thereof.

9 . A non-transitory computer readable medium having stored thereon instructions for causing one or more processing units to execute the method according to claim 1 .

10 . A system for determination of a causality based on big data analysis, comprising:

an interface to a network for connecting to a plurality of big data sources;

a processor;

a memory connected to the processor, the memory contains instructions that when executed by the processor, configure the system to:

extract a plurality of unstructured data elements from a plurality of unstructured big data sources;

generate at least one signature for each of the plurality of unstructured data elements;

identify at least one common pattern within the signatures of the plurality of unstructured data elements;

match the at least one common pattern to at least one hypothesis by comparing at least one signature of the common pattern to at least one hypothesis; and

determine the causality of the at least one common pattern based on the at least one hypothesis matching the at least one common pattern.

11 . The system of claim 10 , wherein the system is further configured to:

generate the at least one signature for the at least one hypothesis.

12 . The system of claim 10 , wherein the system is further configured to:

cluster the signatures identified to have common patterns; and

correlate the generated clusters to identify associations between their respective identified common patterns.

13 . The system of claim 10 , wherein the system is further configured to:

correlate the at least one hypothesis matching the at least one common pattern.

14 . The system of claim 10 , wherein the system is further configured to:

compute a matching score based on the comparisons of the signatures;

determine a hypothesis having the highest matching score to be the causality.

15 . The system of claim 10 , wherein the at least one hypothesis is textual content representing a series of natural events, wherein the at least one hypothesis is extracted from big data sources.

16 . The system of claim 10 , wherein the unstructured data element is at least one of: multimedia content, a document, metadata, a collection of health records, analog data, a file, unstructured text, and a web page.

17 . The system of claim 16 , wherein the multimedia content element is at least one of: an image, graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, images of signals, combinations thereof, and portions thereof.

18 . The system of claim 10 , further comprising a database for storing the determined causality.

19 . A method for determining a probability of a hypothesis based on big data analysis, comprising:

receiving a request to check the probability of a hypothesis a hypothesizes;

generating at least one signature to the hypotheses;

crawling through a plurality of relevant big data sources to detect unstructured data elements;

generating at least one signature for each detected unstructured data element; and

determining the probability of the hypothesis respective of the generated signatures.

20 . The method of claim 19 , further comprising:

matching the at least one signature of the unstructured data element to the at least one generated for of the hypothesis; and

computing the probability based on the matching results.

21 . A non-transitory computer readable medium having stored thereon instructions for causing one or more processing units to execute the method according to claim 13 .