Identifying relevant content for data gathered from real time communications includes obtaining conversational data from a real time communication, identifying contextual data with at least one contextual data source relevant to the real time communication, and inferring a meaning of the conversational data based on the contextual data.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for identifying relevant content for data gathered from real time communications, the method comprising: obtaining conversational data from a real time communication; identifying contextual data with at least one contextual data source relevant to said real time communication; learning patterns and relationships from said conversational data based on said contextual data from an analytical engine; and inferring a meaning of said conversational data based on said contextual data. 2. The method of claim 1, wherein said conversational data includes information from text-based messaging sources, voice sources, graphic sources, video sources, or combinations thereof. 3. The method of claim 1, wherein said contextual data includes at least one contextual data source that contains information about participants, physical resources, a domain taxonomy, an association database, or combinations thereof. 4. The method of claim 1, further comprising: with the analytical engine, analyzing said conversational data based on said contextual data using an analytical technique. 5. The method of claim 4, wherein said analytical technique includes pattern recognition, data analysis, structured and unstructured data analysis, predictive analysis, or combinations thereof. 6. The method of claim 1, further includes referencing a completion data source to provide additional contextual data for said conversational data to further infer said meaning of said conversational data or to provide relevant results. 7. The method of claim 6, wherein said completion data source includes databases that contain information about corporate data warehouses, public internet sources, domain specific databases, or combinations thereof. 8. The method of claim 1, further includes presenting relevant data in an output device. 9. A system for identifying relevant content for data gathered from real time communications, the system comprising: an obtaining engine to obtain conversational data from a real time communication; an identification engine to identify contextual data with at least one contextual data source relevant to said real time communication; an analytical engine to analyze said conversational data based on said contextual data; a learning engine to learn patterns and relationships from said conversational data based on said contextual data from said analytical engine; and an inference engine to infer a meaning of said conversational data based on said contextual data. 10. The system of claim 9, further includes a reference engine to reference a completion data source to provide additional contextual data for said conversational data to further infer said meaning of said conversational data or to provide relevant results. 11. The system of claim 9, wherein said patterns and said relationships are stored in an association database for inferring said meaning of said data gathered from said real time communications in subsequent operations. 12. The system of claim 9, further comprising a presentation engine to present relevant data in an output device. 13. A computer program product for identifying relevant content for data gathered from real time communications, comprising: a tangible computer readable storage medium, said tangible computer readable storage medium comprising computer readable program code embodied therewith, said computer readable program code comprising program instructions that, when executed, causes a processor to: obtain conversational data from a real time communication; identify contextual data with at least one contextual data source relevant to said real time communication; analyze said conversational data based on said contextual data; learn patterns and relationships from said conversational data based on said contextual data based on said analysis; and infer a meaning of said conversational data based on said contextual data. 14. The product of claim 13, further comprising computer readable program code comprising program instructions that, when executed, causes said processor to reference a completion data source to provide additional contextual data for said conversational data to further infer said meaning of said conversational data or provide relevant results. 15. The product of claim 13, further comprising computer readable program code comprising program instructions that, when executed, causes said processor to present relevant data in an output device.