WO2022084792A1

WO2022084792A1 - System and method for providing video response using videobot

Info

Publication number: WO2022084792A1
Application number: PCT/IB2021/059242
Authority: WO
Inventors: Jatin Solanki; Vivek Gupta
Original assignee: Expertrons Technologies Private Limited
Priority date: 2020-10-20
Filing date: 2021-10-08
Publication date: 2022-04-28

Abstract

The present invention discloses a system and method for providing response to the query of a user using videobot. Further, after signing up, the user searches for an expert. After finding the appropriate expert, he selects the expert. Expert's introduction video will be shown to the user on the user interface. Once cue for asking a question appears in the form of audio or visual signal to ask a query, the user asks any question using audio-video input device after tapping the mic icon or tapping on the predetermined query on the user interface. Expert's video response of the query asked is presented for watching.

Description

TITLE OF INVENTION: SYSTEM AND METHOD FOR PROVIDING VIDEO

RESPONSE USING VIDEOBOT

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This patent application claims the priority of the Indian Patent Application No. 202021045788 filed on 20th October, 2020 having the title ‘System And Method For Providing Video Response Using Videobot’, whose contents have been incorporated herein by the way of reference.

FIELD OF INVENTION

[0001] The present invention relates to the field of multimedia. Particularly the invention relates to technology for providing video content using technology. More particularly to a system and method to present responses to a user query in the form of video in real time using videobot.

BACKGROUND OF INVENTION

[0002] With the spread of the online video community and the development of technology for providing video content, users can easily watch and share videos through the network. A User may wish to get answers to his curiosity or requirement through a video by searching on a variety of platforms.

[0003] In addition, various video contents are produced and provided according to the increase of user's desire to produce personalized contents (UGC), and various sites providing video contents such as YouTube can easily display videos to those who produce the video contents. Provides the opportunity to upload and share uploaded videos to other users. However, UGC is always based on the creator's perspective.

[0004] In order to view a desired video content to get answers to a desire to know something specific on a site that provides video content, a user generally searches for video content through keywords. Keyword search is helpful when a user finds the desired video content but a vague answer to his query, most of the time. However, the more irrelevant information are also bound to be consumed, as video has many aspects together. [0005] In order to overcome the limitation of keyword search, various methods for recommending video contents have been proposed. For example, how many users recommend the selected video content as popular content, how to recommend other video contents of the same genre as the user's existing purchase or watched video content, and how the user enters the interested information. However, the profile of a user is also important, as well as the profile of the video creator.

[0006] However, in an environment in which various kinds of video contents are supplied so that even one's own preferences cannot be understood, it is necessary to automatically recommend optimized video contents suitable for a user's inclination. It is difficult to reflect the user's preferences, and recommending video content according to a user's profile. Video recommendation according to the input of interest information has a problem in that it is difficult for the user to correctly grasp his or her preferences or to satisfy the preferences of the users.

[0007] Furthermore, even if the same kind of content is recommended, the classification criteria of the creator are applied to classify the various contents by type, but the user's personal classification criteria cannot be reflected, so the recommended video contents for each individual does not satisfy the user's preference.

[0008] US Patent Publication No. US20200053424 discloses a process that adapts user- initiated search queries. The process executes at a client device with a microphone. The process downloads audio fingerprints from a remote server for a plurality of video programs, and downloads information that correlates the audio fingerprint to the video programs. The process matches a sample audio fingerprint to a locally stored audio fingerprint and uses the correlating information to identify a first video program corresponding to the matched sample audio fingerprint. The process then receives user input to initiate a search query. The process provides auto-complete suggestions for the search query based on the first video program.

[0009] US Patent No. 8,595,226, discloses a method and system for providing content according to personal preference, refers to a user requesting a category of video content, and if the category or subcategory of the category corresponds to a preference tag set by the user, Disclosed is a method for providing video content according to a preference score based on access frequency, a preference level, etc. of a video content of a category requested by the user. According to this method, there is an effect that can recommend video content reflecting the user's preferences, but not only the user needs to input the preference tag in advance, but also the user's mood or preference change that the recommended video content changes from time to time. There was a problem of not responding adaptively.

[0010] The user likes to ask a query and wants a real time response, more like an interaction to grasp the concept and education imparted. The one on one interaction is possible through the technology, where the user can feel like interacting and getting the response to their query.

[0011] Every individual has a different mental level and query stimulated in the brain is different. Whereas the flow of information in a video is as per the choice of creator and not at the preference of the user. Also, the question-answer does not feel like interaction, which leads to attention lapse and loss of interest.

[0012] Accordingly, in spite of above available resources to overcome the aforementioned problems inherent in the existing solutions for resolving the user's queries with real time user interaction, there exists a need for a system and method for catering the user's queries and provide an adequate response to said queries through a video. Which will enable the user to get focused education and required training to achieve a desired result.

SUMMARY OF INVENTION

[0013] The present invention discloses a system and method for providing video response to the query of an user through videobot.

[0014] In one aspect of the invention, wherein after signing up, the user searches for an expert. After finding the appropriate expert, he selects the expert. Expert’s introduction video will be shown to the user on the user interface. Once cue for asking a question appears in the form of audio or visual signal to ask a query, the candidate will ask any question using audio-video input device after tapping the mic icon or tapping on the predetermined query on the user interface. Expert’s reply video of the query asked shall play. [0015] In another aspect of the invention comprises of a user interface (110), an AV input device (112), a processor (114), a memory (130), a database (132), a network (134) to record the video and convert the video into videobot to provide response to the query of a user based on the metadata of videobot, user profile data and expert profile data

[0016] In another aspect of the invention the processor (114) comprises a query analysis engine (116) for analysing the query of the user asked through the AV input device 112 or through the user interface 110, a video conversion engine (120) for converting the video content into a videobot based on predetermined format, a tagging engine (118) for tagging the video based on video metadata, a mapping engine (122) fro mapping the user query with the video metadata, a video recommendation engine (124) for providing the recommendation of video based on the user query metadata and an expert recommendation engine (126) for providing list of relevant expert to the user based on the user profile data and the experts profile data.

[0017] In still another aspect of the invention the system obtains one or more videos from the experts through the AV input device 112. The processor identifies the contents in the videos content through analysing the video and the information provided by the expert. Further, the video conversion engine 120 converts video into videobot based on the predetermined format and analyses video to get metadata. Furthermore, the tagging engine 118 tags video metadata and experts profile data with videobot. Moreover, the system receives a query from the user through the AV input device 112 or the user interface 110. Further, the Query analysis engine 116 extracts metadata from said query. Furthermore, mapping engine 122 maps data of the videobot and user profile along with user query and the video recommendation engine 124 presents relevant video as response to the user query for the user to watch on the user interface 110.

[0018] In yet another aspect of the invention the system utilises an Al module 128 to provide suitable response to the user query based on historical data and user behaviour on the recommended videobot responses.

BRIEF DESCRIPTION OF DRAWINGS

[0019] These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:

FIG. l is a block diagram of the System for providing video content using videobot, in accordance with an aspect of the present technique;

FIG. 2 is a flowchart illustrating the method for providing response to the query of a user using video bot, in accordance with an aspect of the present technique;

FIG. 3 is a flowchart illustrating the method for providing response to the query of a user from associated expert using video bot, in accordance with an aspect of the present technique;

FIG. 4 is a flowchart illustrating the method for recommending expert to a user, in accordance with an aspect of the present technique;

FIG. 5 is a flowchart illustrating the method for providing response to the query of a user using video bot without expert data, in accordance with an aspect of the present technique; and

FIG. 6 is a flowchart illustrating the method for Al module of the video bot, in accordance with an aspect of the present technique.

DETAILED DESCRIPTION OF INVENTION

[0020] The following description is full and informative description of the best method presently contemplated for carrying out the present invention which is known to the inventors at the time of filing the patent application. Of course, many modifications and adaptations will be apparent to those skilled in the relevant arts in view of the following description in view of the accompanying drawings and the appended claims. While the system and method described herein are provided with a certain degree of specificity, the present technique may be implemented with either greater or lesser specificity, depending on the needs of the user. Further, some of the features of the present technique may be used to advantage without the corresponding use of other features described in the following paragraphs. As such, the present description should be considered as merely illustrative of the principles of the present technique and not in limitation thereof, since the present technique is defined solely by the claims.

[0021] The present invention relates to the field of multimedia. Particularly the invention relates to technology for providing video content using technology. More particularly to a system and method to present responses to a user query in the form of video in real time using videobot.

[0022] In one embodiment of the invention wherein after signing up, the user searches for an expert. After finding the appropriate expert, he selects the expert. Expert’s introduction video will be shown to the user on the user interface. Once cue for asking a question appears in the form of audio or visual signal to ask a query, the candidate will ask any question using audio-video input device after tapping the mic icon or tapping on the predetermined query on the user interface. Expert’s reply video of the query asked may play for the user to watch. Moreover, the user may tap on a pre provided list of questions on the user interface 110. Further, the user may type questions or can ask through AV input device 112. The expert’s videobot will provide the answer to the query of the user.

[0023] In another embodiment of the invention comprises of a user interface (HO), an AV input device (112), a processor (114), a memory (130), a database (132), a network (134) to record the video and convert the video into videobot to provide response to the query of a user based on the metadata of videobot, user profile data and expert profile data.

[0024] In another embodiment of the invention the processor (114) comprises a query analysis engine (116) for analysing the query of the user asked through the AV input device 112 or through the user interface 110, a video conversion engine (120) for converting the video content into a videobot based on predetermined format, a tagging engine (118) for tagging the video based on video metadata, a mapping engine (122) fro mapping the user query with the video metadata, a video recommendation engine (124) for providing the recommendation of video based on the user query metadata and an expert recommendation engine (126) for providing list of relevant expert to the user based on the user profile data and the experts profile data. [0025] In one embodiment of the invention, the system may include a processor 114 that may be, for example, a central processing unit processor (CPU), a chip or any suitable computing or computational device. The processor 114 (or one or more processors, possibly across multiple units or devices) may be configured to carry out methods described herein, and/or to execute or act as the various modules, units, etc. Further the system may be included in one or more computing devices or act as the components of connected through the network 134. More than one computing device may be included, and one or more computing devices may act as the various components, for example the components of the system as described herein. For example, a plurality of computing devices may be used by a plurality of users connected through the network 134.

[0026] In one embodiment of the invention the user interface 110 is capable of playing video and taking input from the user and displaying information to the user. Further, the AV input device comprises of microphone and camera know in the art.

[0027] In another embodiment of the invention Network 134 may be, may comprise or may be part of a private or public IP network, or the internet, or a combination thereof. Additionally, or alternatively, network 134 may be, comprise or be part of a global system for mobile communications (GSM) network. For example, network 134 may include or comprise an IP network such as the internet, a GSM related network and any equipment for bridging or otherwise connecting such networks as known in the art. In addition, network 134 may be, may comprise or be part of an integrated services digital network (ISDN), a public switched telephone network (PSTN), a public or private data network, a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a wireline or wireless network, a local, regional, or global communication network, a satellite communication network, a cellular communication network, any combination of the preceding and/or any other suitable communication means. Moreover, the database 132 may be operatively connected to the processor 114 through network 134.

[0028] In another embodiment of the invention the memory 130 may be or may include, for example, a Random Access Memory (RAM), a read only memory (ROM), a Dynamic RAM (DRAM), a Synchronous DRAM (SD-RAM), a double data rate (DDR) memory chip, a Flash memory, a volatile memory, a non-volatile memory, a cache memory, a buffer, a short-term memory unit, a long-term memory unit, or other suitable memory units or storage units. Memory 130 may be or may include a plurality of, possibly different memory units. Memory 130 may be a computer or processor non-transitory readable medium, or a computer non-transitory storage medium, e.g., a RAM.

[0029] In another embodiment of the invention, The Al module 128 may utilize any of a variety of technologies, such as probabilistic models, neural networks, machine learning, and the like. Through analyzing the statistical patterns, the feedback data received from the selection made by the user, and the external data, the Al module 128 can generate the best suitable expert and video recommendation. In particular, the Al module 132 may generate rules that optimally provide the suitable expert and video in light of the statistical patterns, the feedback data, and the external data. Upon generating and/or updating the Al module 128, the Al module 128 may store the rules in the database 132.

[0030] FIG. 1 is a block diagram of the System for providing video content using videobot, wherein the user interface 110 is user for displaying video and to take input from the user for asking query as well as providing the user profile data. Further the user interface 110 also provides options to provide expert data and record video using the AV input device 112 connected thereto. The user interface 110 is connected to the processor 114 for processing the data received from the user interface 110 and the AV input device 112. The processor processes the data and stores the data into the database 132 connected with the processor, after tagging and indexing all the data. The network connects the processor 114, the memory 130 and the database 132. Moreover the Al module 128 connected with the processor 114 and the database 132 through the network 134, analyses and provides better recommendation to the user.

[0031] FIG. 2 is a flowchart illustrating the method for providing response to the query of a user using video bot, wherein in the step 210, the system obtains one or more videos from the experts through the AV input device 112. In the step 212, The processor identifies the contents in the videos content through analysing the video and the information provided by the expert. Further, in the step 214, the video conversion engine 120 converts video into videobot based on the predetermined format and analyses video to get metadata. Furthermore, in the step 216, the tagging engine 118 tags video metadata and experts profile data with videobot. Moreover, in the step 218, the system receives a query from the user through the AV input device 112 or the user interface 110. Further, in the step 220, the Query analysis engine 116 extracts metadata from said query. Furthermore, in the step 222, mapping engine 122 maps data of the videobot and user profile along with user query and the video recommendation engine 124 presents relevant video as response to the user query for the user to watch on the user interface 110.

[0032] FIG. 3 is a flowchart illustrating the method for providing response to the query of a user from an associated expert using video hot, wherein the user has selected the relevant expert. In the step 240, the user enters the search query using AV input device 112 or through user interface 110 by tapping on the list of query provided or by writing his own query. Further, in the step 242, the query analysis engine analyses the asked query and extracts metadata from the asked query along with user profile data. In the step 244, the metadata in the videobot and expert profile associated with videobot is identified. Further, in the step 246, the mapping engine 122 identifies metadata in the videobot and associated experts profile to map with the user query. Furthermore, in the step 248, The video recommendation engine 124 provides the video recommendation matching with the user query to present the relevant videobot response to the user.

[0033] FIG. 4 is a flowchart illustrating the method for recommending experts to a user. In the step 260, the tagging engine 118 analyses the user profile and in the step 262, experts profiles to tag metadata of the profiles. The profile data set ranges from the educational, vocation, location, career, hobby and other profiling data known in the art. The mapping engine 122 maps between the user profile data with the available expert profile data in the database 132 to provide a score of match. In the step 264, The expert recommendation engine 126 recommends experts based on the mapping score of the user profile data and expert profile data. Further, the user gets recommendations from experts relevant to his profile, wherein in the step 266, the user selects the most suitable expert for him. Moreover, the tagging engine 118 tags the user profile with the expert profile for future recommendation of videobot response to the user query. In the step 268, the video recommendation engine 124 gives preference to the tagged expert’s videobot response for the user’s query.

[0034] FIG. 5 is a flowchart illustrating the method for providing response to the query of a user using video bot without expert data. In the step 280, the system takes the user profile input data and when in the step 282, the user asks a query through AV input device 112 or through user interface 110. Further, in the step 284, the video recommendation engine 124 provides a list of videobot responses based on the mapping of query metadata and user profile data with the videobot metadata. Moreover, in the step 286, the user selects a videobot and watches the response on the user interface.

[0035] FIG. 6 is a flowchart illustrating the method for Al module of the video bot. The Al module 128 may utilize any of a variety of technologies, such as probabilistic models, neural networks, machine learning, and the like. Through analyzing the statistical patterns, the historical data behaviour of the user and user adjustment data in the form of feedback data received from the selection made by the user Al planned program may generate the rules for recommending best suitable expert and video.

[0036] In another aspect of the invention, the method of videobot system is a computer implemented method for providing video response to a user query using videobot, the method comprises of receiving inputs from the user by a user interface (110) or through an AV input device, processing data received from the user by a processor (114) connected to the user interface (112); analysing the query of the user received through the AV input device 112 or the user interface 110 by a query analysis engine (116); converting video content recorded by an expert through AV input device (112) into a videobot based on predetermined format by a video conversion engine (120); tagging the video content based on video metadata and the expert profile data, a mapping engine (122) for mapping the analysed query with the video metadata by a tagging engine (118); providing the recommendation of video based on the mapped query metadata with video metadata by a video recommendation engine (124); and watching recommended video by the user on the user interface (110).

[0037] In another aspect of the invention, the computer implemented method has a step wherein the user receives a list of recommended excerpts, to select one or more experts relevant to the user, based on the user profile data and the experts profile data by an expert recommendation engine (126) of the processor (114); wherein videobot response of the selected expert is provided on priority to the user for response to a query by the video recommendation engine (124). Further, the video recommendation engine (124) provides video based on mapping data received from the mapping engine (122) based on mapping of the analysed query and user profile data with the video metadata and expert profile data; wherein the video is provided in the form of list or playing one of the recommended video on the user interface (110). Furthermore, the computer implemented method has step wherein recommending the video to the user uses an Al module (128) having an Al planned program for better recommendation of video and expert to the user, in which an Al algorithm being trained to classify data stream based on historical information related to the user and experts including historical user behaviour, selection made by the user, which is stored in the database (132) in an indexed format. Moreover, the computer implemented method is performed in a way wherein the steps are performed by components at one integrated system or components are at different places connected through the network (134) without requiring any component being connected through hardware components.

[0038] In another embodiment of the invention the system for providing video response to a user query using videobot, the system comprises of a user interface (110) adapted to receive inputs from the user and watching video, a processor (114) connected to the user interface for processing data received from the user, an AV input device (112) adapted to receive audio video input from the user, a memory (130) adapted to store data for processing the stored data , a database (132) adapted to store intex data, a network (134) adapted to connect the processor (114) with database and an Al module (128); characterise in that the processor (114) comprises a query analysis engine (116) for analysing the query of the user received through the AV input device 112 or the user interface 110; a video conversion engine (120) for converting video content recorded by an expert through AV input device (112) into a videobot based on predetermined format; a tagging engine (118) for tagging the video content based on video metadata and the expert profile data; a mapping engine (122) for mapping the analysed query with the video metadata, and a video recommendation engine (124) for providing the recommendation of video based on the mapped query metadata with video metadata for the user to watch on the user interface.

[0039] In another embodiment of the invention the processor (114) comprises an expert recommendation engine (126) for providing a list of relevant experts to the user based on the user profile data and the experts profile data, to select one or more experts relevant to the user,; wherein videobot response of the selected expert is provided on priority to the user for response to a query by the video recommendation engine (124). Further, the video recommendation engine (124) provides video based on mapping data received from the mapping engine (122) based on mapping of the analysed query and user profile data with the video metadata and expert profile data; wherein the video is provided in the form of list or playing one of the recommended video on the user interface (110). Furthermore, the Al module (128) uses Al planned program for better recommendation of video and expert to the user, in which an Al algorithm being trained to classify data stream based on historical information related to the user and experts including historical user behaviour, selection made by the user, which is stored in the database (132) in an indexed format. Moreover, the components are at different places connected through the network (134) without requiring any component being connected through hardware components.

[0040] In another embodiment of the invention the method for video response to a user query using videobot, the method comprises of receiving inputs from the user by a user interface (110) or through an AV input device, processing data received from the user by a processor (114) connected to the user interface (112); analysing the query of the user received through the AV input device 112 or the user interface 110 by a query analysis engine (116); converting video content recorded by an expert through AV input device (112) into a videobot based on predetermined format by a video conversion engine (120); tagging the video content based on video metadata and the expert profile data; a mapping engine (122) for mapping the analysed query with the video metadata by a tagging engine (118); providing the recommendation of video based on the mapped query metadata with video metadata by a video recommendation engine (124); and watching recommended video by the user on the user interface (110)

[0041] In another embodiment of the invention the user receives a list of recommended excerpts, to select one or more experts relevant to the user, based on the user profile data and the experts profile data by an expert recommendation engine (126); wherein videobot response of the selected expert is provided on priority to the user for response to a query by the video recommendation engine (124). Further, the video recommendation engine (124) provides video based on mapping data received from the mapping engine (122) based on mapping of the analysed query and user profile data with the video metadata and expert profile data; wherein the video is provided in the form of list or playing one of the recommended video on the user interface (110). Furthermore, recommending the video to the user uses an Al module (128) having an Al planned program for better recommendation of video and expert to the user, in which an Al algorithm being trained to classify data stream based on historical information related to the user and experts including historical user behaviour, selection made by the user, which is stored in the database (132) in an indexed format. Moreover, the steps are performed by components at one integrated system or components are at different places connected through the network (134) without requiring any component being connected through hardware components.

[0042] In another embodiment of the invention a user interface 110 is provided wherein the user can directly get connected with Expert’s video for guidance using videobot. The videobot interaction between a user and expert consists of a videobot of an expert, which will have a like and share option. Further, the user will be able to view the expert’ s profile data and also will be able to connect for other modes of interaction with the user including video chats, calls or through emails. Further in one-one interaction the user interface will enable the user to connect with the expert through live video call.

[0043] In another embodiment of the invention the AV input device 112 may help users to ask the questions to the experts. Whenever a user clicks on the mic icon and asks the question the videobot related to that question will be automatically played. Further, the videos will be played on the basis of questions asked by the user.

[0044] In another embodiment of the invention a user may register on the system through the registration section enabled by the processor 114. The user may provide profile details about him like, education, profession, experience, domain of knowledge, skills, hometown, schools, socio economic factors, religion, race, aspiration, dream, ambition and goals, location, hobbies, certifications, job profile, college, degree, preference in terms of company, department job profile and other profiling data known in the art. The system may provide guidance related to education and career using videobot.

[0045] In another embodiment of the invention an expert has to register by providing the expert profile data. The expert may create a videobot using the system for guiding users for their Dream Job, Dream B school, Dream Business, Dream Startup, Dream Education. [0046] In another embodiment of the invention the expert may provide small videos with tags relevant to the question being answered in the video. Further, the videos can be for education, experience, life journey or any other relevant issues or query a user may ask. Furthermore, the video is recorded by the expert using the AV input device 112 and the video conversion engine 120 processes and converts the video into videobot. After processing the video into videobot, it is now live for users to watch.

[0047] In yet another embodiment of the invention, the system of videobot providing response to the user query can be integrated on website or mobile application, where a user can chat with the expert by asking query through AV input device 112 or by tapping on the customised list of query available or typing the query on user interface 110. The response is provided in the form of video on the user interface 110 in the form of real time interaction pattern. The invention can be used for education, counselling, training, skill development and providing responses to specific or general queries related to other domains.

[0048] The following description is presented to enable a person of ordinary skill in the art to make and use the invention and is provided in the context of the requirement for obtaining a patent. The present description is the best presently-contemplated method for carrying out the present invention. Various modifications to the preferred embodiment will be readily apparent to those skilled in the art and the generic principles of the present invention may be applied to other embodiments, and some features of the present invention may be used without the corresponding use of other features. Accordingly, the present invention is not intended to be limited to the embodiment shown but is to be accorded the widest scope consistent with the principles and features described herein.

Claims

CLAIMS We Claim:

1. A system for providing video response to a user query using videobot, the system comprises of a user interface (110) adapted to receive inputs from the user and watching video, a processor (114) coupled to the user interface for processing data received from the user, an AV input device (112) adapted to receive audio video input from the user, a memory (130) adapted to store data for processing the stored data , a database (132) adapted to store index data, a network (134) adapted to connect the processor (114) with database and an Al module (128); characterise in that the processor (114) comprises a query analysis engine (116) for analysing the query of the user received through the AV input device 112 or the user interface 110; a video conversion engine (120) for converting video content recorded by an expert through AV input device (112) into a videobot based on predetermined format; a tagging engine (118) for tagging the video content based on video metadata and the expert profile data; a mapping engine (122) for mapping the analysed query with the video metadata, and a video recommendation engine (124) for providing the recommendation of video based on the mapped query metadata with video metadata for the user to watch on the user interface.

2. The system as claimed in claim 1, wherein the processor (114) comprises an expert recommendation engine (126) for providing a list of relevant experts to the user based on the user profile data and the experts profile data, to select one or more experts relevant to the user,; wherein videobot response of the selected expert is provided on priority to the user for response to a query by the video recommendation engine (124).

3. The system as claimed in claim 1, wherein the video recommendation engine (124) provides video based on mapping data received from the mapping engine (122) based on mapping of the analysed query and user profile data with the video metadata and expert profile data; wherein the video is provided in the form of list or playing one of the recommended video on the user interface (110).

4. The system as claimed in claim 1, wherein the Al module (128) uses Al planned program for better recommendation of video and expert to the user, in which an Al algorithm being trained to classify data stream based on historical information related to the user and experts including historical user behaviour, selection made by the user, which is stored in the database (132) in an indexed format.

5. The system as claimed in claim 1, wherein the components are connected as an integrated system or at different places connected through the network (134) without requiring any component being connected through hardware components.

6. A method for providing video response to a user query using videobot, the method comprises of receiving inputs from the user by a user interface (110) or through an AV input device, processing data received from the user by a processor (114) connected to the user interface (112); analysing the query of the user received through the AV input device 112 or the user interface 110 by a query analysis engine (116); converting video content recorded by an expert through AV input device (112) into a videobot based on predetermined format by a video conversion engine (120); tagging the video content based on video metadata and the expert profile data, a mapping engine (122) for mapping the analysed query with the video metadata by a tagging engine (118); providing the recommendation of video based on the mapped query metadata with video metadata by a video recommendation engine (124); and watching recommended video by the user on the user interface (110).

7. The method as claimed in claim 6, wherein the user receives a list of recommended excerpts, to select one or more experts relevant to the user, based on the user profile data and the experts profile data by an expert recommendation engine (126) of the processor (114); wherein videobot response of the selected expert is provided on priority to the user for response to a query by the video recommendation engine (124).

8. The method as claimed in claim 6, wherein the video recommendation engine (124) provides video based on mapping data received from the mapping engine (122) based on mapping of the analysed query and user profile data with the video metadata and expert profile data; wherein the video is provided in the form of list or playing one of the recommended video on the user interface (110).

9. The method as claimed in claim 6, wherein recommending the video to the user uses an Al module (128) having an Al planned program for better recommendation of video and expert to the user, in which an Al algorithm being trained to classify data stream based on historical information related to the user and experts including historical user behaviour, selection made by the user, which is stored in the database (132) in an indexed format.

10. The method as claimed in claim 6, wherein the steps are performed by components at one integrated system or components are at different places connected through the network (134) without requiring any component being connected through hardware components.

11. A computer implemented method for providing video response to a user query using videobot, the method comprises of receiving inputs from the user by a user interface (110) or through an AV input device, processing data received from the user by a processor (114) connected to the user interface (112); analysing the query of the user received through the AV input device 112 or the user interface 110 by a query analysis engine (116); converting video content recorded by an expert through AV input device (112) into a videobot based on predetermined format by a video conversion engine (120); tagging the video content based on video metadata and the expert profile data, a mapping engine (122) for mapping the analysed query with the video metadata by a tagging engine (118); providing the recommendation of video based on the mapped query metadata with video metadata by a video recommendation engine (124); and watching recommended video by the user on the user interface (110).

17

12. The computer implemented method as claimed in claim 11, wherein the user receives a list of recommended excerpts, to select one or more experts relevant to the user, based on the user profile data and the experts profile data by an expert recommendation engine (126) of the processor (114); wherein videobot response of the selected expert is provided on priority to the user for response to a query by the video recommendation engine (124).

13. The computer implemented method as claimed in claim 11, wherein the video recommendation engine (124) provides video based on mapping data received from the mapping engine (122) based on mapping of the analysed query and user profile data with the video metadata and expert profile data; wherein the video is provided in the form of list or playing one of the recommended video on the user interface (110).

14. The computer implemented method as claimed in claim 11, wherein recommending the video to the user uses an Al module (128) having an Al planned program for better recommendation of video and expert to the user, in which an Al algorithm being trained to classify data stream based on historical information related to the user and experts including historical user behaviour, selection made by the user, which is stored in the database (132) in an indexed format.

15. The computer implemented method as claimed in claim 11, wherein the steps are performed by components at one integrated system or components are at different places connected through the network (134) without requiring any component being connected through hardware components.

18