2. The method of claim 1 wherein the user psychographic data includes indicia of the corresponding user's interests, activities and/or opinions.
1. A computer-implemented method for understanding the meaning of an object given its unstructured textual description and using that understanding together with a user's demographics to retrieve other demographically and psychographic similar objects stored in an index, comprising the steps of: provisioning a server coupled to a network for communications; indexing a large corpus of anonymous demographic data defined at multiple levels of granularity; indexing a large knowledge corpus of encyclopedic text articles to form a content vector space defined by the text content; indexing knowledge corpus of encyclopedic text article categories and their interconnections to form a category space defined by a set of categories; storing in a datastore accessible to the server, data representing the content of the text articles represented as an inverted index; storing in a datastore accessible to the server, data representing the category space represented as a directed cyclic graph; acquiring individual location associated with each one of a plurality of remote users over the communications network; acquiring text data associated with each one of the plurality of remote users over the communications network; acquiring, directly, psychographic data associated with each one of the plurality of remote users over the communications network; projecting the location data associated with each one of the plurality of remote users over the communications network onto the demographic knowledge base to infer their demographic data; projecting the text data associated with each one of the plurality of remote users over the communications network onto the encyclopedic knowledge base to infer their similarity data; projecting the acquired user text data on to the defined category space to infer psychographic data, including representing each user's characteristics as an n-dimensional concept vector based on the said category space, each dimension having a binary value for including, or conversely excluding, the corresponding category; receiving data at the server associated with an object for matching the object to at least one of the remote users, wherein the object data includes at least minimal demographic data and psychographic data associated with the object; projecting the received psychographic object data on to the defined category space, including representing the object as an n-dimensional concept vector; determining a first similarity metric for each user relative to the object, based on the corresponding demographic data; estimating a second similarity metric for each user relative to the object, based on the corresponding n-dimensional concept vectors; and matching the object to at least one of the users based on a weighted combination of the first and second similarity metrics.