12. A context-based co-operative learning method, comprising: identifying and indexing objects in accordance with pre-determined parameters of identification and indexing, using an identifier; defining parameters of identification in order to determine context topic and/or context theme of the objects based on identifiable features of the objects, using a context determinator; gathering sources of information in relation to or with reference to the identified objects, using an information sources gatherer; searching for the objects, in response to at least a user query, within the determined context topic and/or the determined context theme, using a searcher; building clusters of relevant objects and further adapted to build at least a cluster library based on pre-defined parameters of clustering the clusters, using a cluster data builder; mapping at least a context of the query for the searcher with the clusters from the cluster library to segregate and poll the objects in response to the search query in line with at least a determined context topic and/or the determined context theme, using a context mapper; and allowing multiple systems to co-operatively learn from each other based on determined context topic and/or determined context theme, using a co-operative learner.
15. The method of claim 12 , wherein the defining parameters of identification includes determining a topic with a topic determinator based on at least one of, top frequency unigrams, top frequency bigrams, longer key phrases, an association among frequently occurring unigrams and frequently occurring bigrams, a corpus of frequent objects and their statistical association leading to most relevant pre-known topics, a likelihood and reinforcement learning mechanisms in order to learn a new topic if there is no pre-known relevant topic, semi-supervised learning mechanisms in order to learn a new topic, and a mapping of key phrases to a pre-known or learnt topic.