SYSTEM AND METHOD FOR PROVIDING CUSTOMIZED APPLICATIONS ON DIFFERENT DEVICES
A method for providing a customized application on different requesting device types of a user is provided. The method enables, firstly, receiving requests made by the user using the different device types over multiple communication channels. Secondly, the method enables assigning a rank to the user based on requests received and one or more rules. Further the method enables determining personalization information based on the ranking. Finally, the method enables rendering a customized application on the different device types based on the personalization information and configuration information stored in a central data repository. The configuration information is related to the application and features thereof based on the user's subscription profile.
1 . A method for providing a customized application on different requesting device types of a user, the method comprising the steps of:
receiving requests made by the user using the different device types over multiple communication channels;
assigning a rank to the user based on requests received and one or more rules;
determining personalization information based on the ranking; and
rendering a customized application on the different device types based on the personalization information and configuration information stored in a central data repository, wherein the configuration information is related to the application and features thereof based on the user's subscription profile.
2 . The method of claim 1 further comprising the step of storing the requests in the central data repository.
3 . The method of claim 1 further comprising the step of monitoring requests made by the user using the different device types over multiple communication channels.
4 . The method of claim 1 , wherein the multiple communication channels comprises at least one of: internet, wireless network capable of data exchange such as General Packet Radio Service (GPRS), Enhanced Data for Global Evolution (EDGE), High-Speed Packet Access (HSPA), Evolution Data Optimized (EvDO), Long-Term Evolution (LTE), Worldwide Interoperability for Microwave Access (WiMAX), Wireless Fidelity (WiFi), High Speed digital cable, Direct to Home (DTH) TV and Internet Protocol Television (IPTV) and any other type of over the air wireless network.
5 . The method of claim 1 , wherein the different requesting device types comprises at least one of: Television (TV), Mobile Phone and Personal Computer (PC).
6 . The method of claim 1 , wherein the requests comprises at least one of: browsing a website from a PC, surfing channels in a TV and making Short Messaging Service (SMS) requests using a mobile phone.
7 . The method of claim 1 , wherein the application comprises any one of a web-based application, a mobile-based application, a television-based application, gaming application etc.
8 . The method of claim 1 , wherein the configuration information comprises information related to the application or features thereof based on user and service provider preferences.
9 . The method of claim 1 , wherein the configuration information comprises information related to reordering of application and features thereof based on user's usage information.
10 . The method of claim 1 , wherein the step of assigning a rank to the user based on requests received and one or more rules comprises:
categorizing the requests into a plurality of interest areas;
assigning a rank to each interest area; and
incrementing the rank based on determination of the number of times requests are made corresponding to each interest area in a predetermined time period.
11 . The method of claim 10 , wherein the predetermined time period comprises requests made by the user within six hours, twelve hours, twenty four hours etc.
12 . The method of claim 10 further comprising the step of tagging the user to a specific interest area.
13 . The method of claim 1 further comprising the steps of :
identifying access patterns of one or more users;
determining one or more rules dynamically using machine learning techniques to classify the one or more users into one or more interest areas based on the access patterns; and
assigning a rank to each user based on the classification.
14 . The method of claim 13 , wherein the step of identifying access patterns of one or more users comprises using information from at least one of: web server logs, TV viewing information and mobile phone usage information related to the one or more users.
15 . The method of claim 13 , wherein the step of determining one or more rules dynamically using machine learning techniques to classify the users into one or more interest areas based on the access patterns comprises identifying users with any of similar: web server log information, TV viewing information and mobile phone usage information.
16 . The method of claim 1 , wherein the step of determining personalization information comprises applying predetermined rules based on the ranking to determine level of personalization of the user.
17 . The method of claim 1 , wherein the step of rendering a customized application on the different device types based on the personalization and configuration information comprises generating a customized user interface layout.
18 . A system for providing a customized application on different requesting device types of a user, the system comprising:
an Adaptive Application & Feature Configuration (AAFC) module configured to facilitate maintaining configuration information related to the applications and features thereof based on the users subscription profile and further configured to rank the user based on requests made by the user using different device types and one or more rules; and
a Service Delivery & User Interface Rendering Platform (SDUIRP) in communication with the AAFC configured to determine personalization information of the user based on the ranking and provide a customized application to the user on different requesting device types based on the personalization and configuration information.
19 . The system of claim 18 , wherein the AAFC comprises an administrator user interface configured to receive configuration information related to the applications and features thereof and further configured to store the configuration information in a central data repository.
20 . The system of claim 18 , wherein the AAFC comprises a user profile module configured to receive and process requests made by the user using the different device types and further configured to store the request in a central data repository.
21 . The system of claim 18 , wherein the AAFC comprises a ranking engine configured to:
categorize the requests into a plurality of interest areas;
assign a rank to each interest area; and
increment the rank based on determination of the number of times requests are made corresponding to each interest area in a predetermined time period.
22 . The system of claim 21 , wherein the predetermined time comprises requests made by the user within six hours, twelve hours, twenty four hours etc.
23 . The system of claim 18 , wherein the AAFC comprises a ranking engine which further comprises a smart analytics engine configured to facilitate the ranking engine to:
identify access patterns of one or more users;
determine one or more rules dynamically using machine learning techniques to classify the users into one or more interest areas based on the access patterns; and
assign a rank to each user based on the classification.
24 . The system of claim 18 , wherein the AAFC comprises a ranking engine which further comprises a smart analytics engine configured to facilitate the ranking engine to:
analyze one or more user requests across the different device types at predetermined intervals of time;
add new interest areas to an existing list of interest areas dynamically using machine learning techniques for classifying similar users from amongst the one or more users into the new interest areas based on the analysis; and
assign a rank to each user based on the classification.
25 . The system of claim 24 , wherein the one or more users correspond to any of existing users and new users.
26 . The system of claim 24 , wherein the smart analytics engine is further configured to refine one or more fixed broad interest areas into specific interest areas or merge one or more fixed specific interest areas into one or more broad interest areas based on the analysis.
27 . The system of claim 24 , wherein the smart analytics engine is further configured to:
analyze one or more user requests across the different device types of the one or more users; and
classify similar users from amongst the one or more users into one or more fixed interest areas.
28 . The system of claim 18 , wherein the SDUIRP is further configured to:
monitor the requests made by the user over multiple communication channels; and
transmit the requests to the AAFC.
29 . The system of claim 18 , wherein the SDUIRP is further configured to provide information related to the user and the type of requesting device to the AAFC.
30 . The system of claim 18 further comprising an applications module configured to send the configuration information to the AAFC electronically in an XML file.
31 . The system of claim 18 further comprising a business logic layer configured to facilitate the SDUIRP to retrieve the configuration information and ranking information from a central data repository.
32 . The system of claim 18 , wherein the different requesting device types comprises Television (TV), Mobile Phone and Personal Computer (PC).
33 . The system of claim 18 , wherein the different requesting device types further comprises at least one of: desktop or laptop with access to internet, high end mobile devices capable of exchanging data, Open Cable Application Platform (OCAP), Enhanced TV Binary Interchange Format (EBIF) based digital cable TV, Direct to Home (DTH) TV and any IPTV based system.