Content personalized for a user is presented. Particularly, content is personalized and presented to a user in a more cognitive and user-understandable manner to improve the impact and the effectiveness on the user. The system utilizes artificial intelligence to analyze and categorize the content and thereby learns to discover the core concept of the content and any patterns involved. The system also understands the user's interests by capturing the preferred presentation formats and the user's past knowledge. The system maps the categorized content and user's interests and personalizes the content and renders into user preferred presentation type and format. The system supplements the main presentation type with additional related content. The system is capable of continuously monitoring the user activities to understand the effectiveness of the presented content type and formats, and feedback is exploited to continuous improvement of presented content and presentation type and formats.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method for presenting content personalized for a user comprising: analyzing and categorizing the content by a server computer using artificial intelligence and storing the categorized content on a memory of the server computer; determining the user's interests and prior knowledge of the user by capturing the user data, user's preferences about content type, presentation type and formats at the server computer, and storing the captured data, data related to user's interests and prior knowledge on the memory of the server computer; mapping the categorized content to user's interests and prior knowledge to discover the content, relevant to user, by the server computer, from the categorized content; and processing the relevant content into a preferred presentation type and format at the server computer and presenting to the user on a user device. 2. The method according to claim 1, wherein analyzing and categorizing the content is carried out by Natural Language Processing (NLP) techniques at the server computer. 3. The method according to claim 2, wherein Natural Language Processing (NLP) techniques include at least one from the semantic analysis, spatial analysis, chronological analysis, conceptual analysis, quantitative analysis, pattern analysis. 4. The method according to claim 1, wherein the user data includes at least one among the user's education, working field, profile input by the user, user's history, past contents presented to the user. 5. The method according to claim 1, wherein mapping the categorized content to user's interests comprises comparing the content concepts with user's interests. 6. The method according to claim 1, wherein mapping the categorized content to user's prior knowledge comprises determining the similarities and differences with the user's prior knowledge. 7. The method according to claim 1, wherein the presentation type comprises at least one among the Text data, Graphical representation, Images, Concept map, Flow charts, Text to speech, Bulleted list, display of trends, patterns in the content. 8. The method according to claim 1, further comprising: translating the relevant content into at least one user preferred language for presenting to the user on the user device. 9. The method according to claim 1, further comprising: presenting analogies and compare and contrast information on the user device based on user's prior knowledge. 10. The method according to claim 1, further comprising: monitoring user's activity by the analytics module during the presentation of content, collecting the monitored user's activity data and user's feedback through user device on the effectiveness of presented content type, presentation type and formats and updating the user's interests on the memory of the server computer based on the data and the feedback collected. 11. The method according to claim 10, wherein the monitored user's activity data comprises at least one among the click events, download events, usability analysis, reading time and scroll data. 12. The method according to claim 10, wherein the user's feedback comprises at least one among the user rating, answers for questions on content type, presentation type and formats output through the user device. 13. The method according to claim 10, further comprising: presenting on the user device the most relevant content with a most preferred presentation type and formats based on the updated user's interests on the memory of server computer. 14. The method according to claim 1, further comprising: collecting the content related to the core concept of content, presented to the user, from plurality of web sources; presenting the content related to the core concept of content, presented to the user, during content presentation on the user device. 15. The method according to claim 14, where in the content related to core concept of content, presented to the user, comprises links to further readable contents, audio visual contents, social networking platforms and other content to attract the user's attention. 16. The method according to claim 1, further comprising: rendering the content, suitable to present on the user device, by the content presentation module. 17. The method according to claim 16, wherein the user device includes a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a mobile device, a hand held device, a wearable device, a global positioning satellite (GPS) device, a palmtop computer, a laptop computer, a desktop computer, a personal trusted device, a web appliance, and any other communication device. 18. A system for presenting content personalized for a user comprising: a learning module of a server computer for analyzing and categorizing the content using artificial intelligence and storing the categorized content on a memory of a server computer; a training module of the server computer for determining the user's interests, prior knowledge of the user by capturing the user data, user's preferences about content type, presentation type, and formats and storing the captured data, data related to the user's interests and the prior knowledge on the memory of the server computer; a content processing module of the server computer for a. mapping the categorized content to user's interests and prior knowledge to discover the content relevant to the user, from the categorized content, and to discover the preferred presentation type and formats; b. processing the content relevant to the user into a preferred presentation type and format for presenting to the user on a user device a content presentation module of the server computer for rendering the relevant content in a preferred presentation type and format on the user device. 19. The system according to claim 18, wherein the learning module includes Natural Language Processing Engine. 20. The system according to claim 19 wherein the Natural Language Processing Engine includes at least one from a semantic analyzer, a spatial analyzer, a chronological analyzer, conceptual analyzer, quantitative analyzer, pattern analyzer, theme analyzer. 21. The system according to claim 18, wherein the user data includes at least one among the user's education, working field, profile input by the user, user's history, past contents presented to the user. 22. The system according to claim 18, wherein mapping the categorized content to user's interests comprises comparing the content concepts with user's interests. 23. The system according to claim 18, wherein mapping the categorized content to prior knowledge of the user comprises determining the similarities and the differences with the prior knowledge of the user. 24. The system according to claim 18, wherein the presentation type comprises at least one among the Text data, Graphical representation, Images, Concept map, Flow charts, Text to speech, Bulleted list, display of trends, patterns in the content. 25. The system according to claim 18, further comprising: language translators for translating the relevant content into at least one user preferred language for presenting to the user. 26. The system according to claim 18, further comprising: presenting analogies and compare and contrast information on the user device base on the prior knowledge of the user. 27. The system according to claim 18, further comprising: an analytics module for monitoring user's activity during the presentation of content, collecting the monitored user's activity data and the user's feedback through the user device on the effectiveness of the presented content type, presentation type and format and updating the user's interests on the memory of the server computer based on the data and the feedback collected. 28. The system according to claim 27, wherein the monitored user's activity data comprises at least one among the click events, download events, usability analysis, reading time and scroll data. 29. The system according to claim 27, wherein the user's feedback comprises at least one among the user rating, answers for questions on content type, presentation type and formats. 30. The system according to claim 27, wherein the presentation module presents on the user device the most relevant content with a most preferred presentation type and formats, based on the updated user's interests. 31. The system according to claim 18, further comprising: a searching module of the server computer for collecting the content related to core concept of content, presented to the user, from plurality of web sources for further presenting to the user during content presentation on the user device. 32. The system according to claim 31, where in the content related to the core concept of content, presented to the user, comprises links to further readable contents, audio visual contents, social networking platforms and other content to attract the user's attention. 33. The system according to claim 31, wherein the presentation module of the server computer further comprises multi-device renderers to present the content on the user device. 34. The system according to claim 33, wherein the user device comprises: a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a mobile device, a hand held device, a wearable device, a global positioning satellite (GPS) device, a palmtop computer, a laptop computer, a desktop computer, a personal trusted device, a web appliance, or any other communication device. 35. A non-transitory computer readable storage medium, comprising instructions to perform the steps of: analyzing and categorizing the content by a server computer using artificial intelligence and storing the categorized content on a memory of the server computer; determining the user's interests, prior knowledge of the user by capturing the user data, user's preferences about content type, presentation type and formats at the server computer, and storing on the memory of the server computer; mapping the categorized content to user's interests and prior knowledge to discover the content relevant to user, by the server computer, from the categorized content, and preferred presentation type and formats; processing the relevant content into a preferred presentation type and format at the server computer and presenting to the user on a user device; monitoring user's activities during the presentation by an analytics module, collecting the monitored user's activity data and the user's feedback through the user device on the effectiveness of presented content type, presentation type and formats and updating the user's interests on the memory of the server computer based on the data and the feedback collected; and presenting on the user device the most relevant content with a most preferred presentation type and formats based on the updated user's interests. 36. The non-transitory computer readable storage medium according to claim 35, further comprising: gathering the content related to the core concept of content, presented to the user, from plurality of web sources; and presenting the content related to the core concept of content presented to the user during content presentation on the user device.