10. A computer implemented method for operating context-sensitive databases, the method comprising: receiving a user selection of one of a plurality of contexts; determining one or more predefined concepts associated with the one of the plurality of contexts from a representation of a structured web community stored in a database, the structured web community comprising a plurality of contexts, each context comprising a set of content, the set of content included in each context determined using a community finding method based on structural closeness and semantic closeness of the content in the context, each context including an array of predefined concepts generated based on terms extracted from the set content in the context and statistical frequency of occurrence of terms within the set of content in the context, each predefined concept characterized by a pattern of terms derived from the set of content in the context, wherein a plurality of the plurality of contexts are associated together to form a hierarchy of overlapping contexts; associating an advertisement with the one of the plurality of contexts based on the at least one predefined concept; and presenting the advertisement in response to the user selection of the one of the plurality of contexts; wherein determining the set of content in each context using a community finding method based on structural closeness and semantic closeness of the content comprises: selecting a node in a network as a source node; computing a set of local communities for the source node; identifying a set of nodes in the set of local communities having a weight greater than a threshold; generating a strong local community for the source node including only the set of nodes that have a weight greater than the threshold; storing the strong local community as one of a plurality of communities of the network; removing the set of nodes in the strong local community and edges connected to the set of nodes from the network to generate a reduced network; selecting a node in the reduced network as a second source node; generating a second strong local community for the second source node, the second strong local community comprising a second set of nodes; storing the second strong local community as one of the plurality of communities of the network; removing the second set of nodes in the second strong local community from the network to generate a second reduced network; repeating the selecting, generating, storing and removing until a reduced network is generated that comprises only nodes with a degree less than a threshold value; and labeling the set of stored strong local communities as one of a disjoint community structure of the network or an overlapping community structure of the network.
10. A computer implemented method for operating context-sensitive databases, the method comprising: receiving a user selection of one of a plurality of contexts; determining one or more predefined concepts associated with the one of the plurality of contexts from a representation of a structured web community stored in a database, the structured web community comprising a plurality of contexts, each context comprising a set of content, the set of content included in each context determined using a community finding method based on structural closeness and semantic closeness of the content in the context, each context including an array of predefined concepts generated based on terms extracted from the set content in the context and statistical frequency of occurrence of terms within the set of content in the context, each predefined concept characterized by a pattern of terms derived from the set of content in the context, wherein a plurality of the plurality of contexts are associated together to form a hierarchy of overlapping contexts; associating an advertisement with the one of the plurality of contexts based on the at least one predefined concept; and presenting the advertisement in response to the user selection of the one of the plurality of contexts; wherein determining the set of content in each context using a community finding method based on structural closeness and semantic closeness of the content comprises: selecting a node in a network as a source node; computing a set of local communities for the source node; identifying a set of nodes in the set of local communities having a weight greater than a threshold; generating a strong local community for the source node including only the set of nodes that have a weight greater than the threshold; storing the strong local community as one of a plurality of communities of the network; removing the set of nodes in the strong local community and edges connected to the set of nodes from the network to generate a reduced network; selecting a node in the reduced network as a second source node; generating a second strong local community for the second source node, the second strong local community comprising a second set of nodes; storing the second strong local community as one of the plurality of communities of the network; removing the second set of nodes in the second strong local community from the network to generate a second reduced network; repeating the selecting, generating, storing and removing until a reduced network is generated that comprises only nodes with a degree less than a threshold value; and labeling the set of stored strong local communities as one of a disjoint community structure of the network or an overlapping community structure of the network. 14. The method of claim 10 , wherein the associating comprises subscribing to a service implementing the method.