# US 2014/0156628 A1 · System and method for determination of causality based on big data analysis > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0156628 A1 - Document ID: US20140156628A1 - Status: Published application - Kind: A1 - Application number: 14/171,158 - Filed: 2014-02-03 - Published: 2014-06-05 - Earliest claimed: 2005-10-26 - Assignees: Cortica, Ltd. - Applicants: Cortica Ltd. - Inventors: Igal Raichelgauz; Karina Odinaev; Yehoshua Y. Zeevi - Web page: https://patentgrep.com/patent/US20140156628A1 ## CPC - G06F 16/906: Clustering; Classification - G06F 16/41: Indexing; Data structures therefor; Storage structures - G06F 16/951: Indexing; Web crawling techniques - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A method and system for determining causality based on big data analysis are provided. The method comprises 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. ## Claims ### Claim 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. ### Claim 2 (depends on 1) The method of claim 1, further comprising: generating the at least one signature for the at least one hypothesis. ### Claim 3 (depends on 1) 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. ### Claim 4 (depends on 1) The method of claim 1, wherein determining the causality further comprises: correlating the at least one hypothesis matching the at least one common pattern. ### Claim 5 (depends on 1) 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. ### Claim 6 (depends on 1) 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. ### Claim 7 (depends on 1) 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. ### Claim 8 (depends on 7) 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. ### Claim 9 (depends on 1) 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. ### Claim 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. ### Claim 11 (depends on 10) The system of claim 10, wherein the system is further configured to: generate the at least one signature for the at least one hypothesis. ### Claim 12 (depends on 10) 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. ### Claim 13 (depends on 10) 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. ### Claim 14 (depends on 10) 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. ### Claim 15 (depends on 10) 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. ### Claim 16 (depends on 10) 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. ### Claim 17 (depends on 16) 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. ### Claim 18 (depends on 10) The system of claim 10, further comprising a database for storing the determined causality. ### Claim 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. ### Claim 20 (depends on 19) 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. ### Claim 21 (depends on 13) 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.