Abstract: Growth of the adoption of an innovation in a social group may be predicted. Web pages are designated in which to search for reference to an innovation, and each of the web pages is associated with one or more stages of innovation adoption. Data are automatically gathered concerning the frequency of reference to the innovation in the individual web pages, statistical information is derived automatically about the innovation's present stage of adoption from the gathered data and from the association of the individual web pages with one or more successive stages of technology development. A prediction of the future growth of the adoption of the innovation is made based on the statistical information.

Abstract: According to one embodiment of the invention, a computerized method used in marketing whole product offerings to clients includes identifying that a first respondent of a client fits into a first segment of a plurality of segments of a technology adoption profile for the client, identifying that a first whole product offering of a company fits into a first phase of a plurality of phases of a technology market development phase model for a plurality of whole product offerings of the company, comparing the first segment to the first phase, and generating an output, based on the comparison, to determine whether to market the first whole product offering to the first respondent.

Abstract: A process is provided for mapping the relationship of the content of a collection of documents (14). The process includes providing a collection (12) of documents (14) where each document (14) includes text. Relevance measures are determined that represent a relevance between each pair of documents (14) based upon the text of the documents (14). A graph (22) is then generated that has nodes (30) and edges (32) with each edge (32) connecting two nodes (30). The graph (22) has a node (30) associated with each document (14) and has an edge (32) connecting nodes (30) for which the relevance measure between associated documents (14) is greater than a specified threshold. In this manner, the graph (22) maps the relationship of the content of the collection (12) of documents (14).

Abstract: A system (10) for recursive document retrieval is provided. An original repository (12) comprises a plurality of documents (14), and a query (16) comprises information by which the original repository (12) can be analyzed to identify relevant documents (14). A retrieval engine (18) is coupled to the original repository (12) and receives the query (16). The retrieval engine (18) is operable to execute an automatic recursive retrieval process with respect to the original repository (12) using the query (16) where the automatic recursive retrieval process comprises a plurality of iterations. The retrieval engine (18) is also operable to provide as system output a retrieved repository (28) comprising a plurality of documents (30) from the original repository (12) identified as sufficiently relevant to the query (16) according to the automatic recursive retrieval process for detection as relevant documents.

Abstract: According to one embodiment of the present invention, a system (10) for arrangement of documents (13) is provided. The system includes a document repository (12) storing a plurality of documents (13). An arrangement engine (14) is coupled to the document repository (12). The arrangement engine (14) is operable to build a plurality of symmetric matrices based upon a plurality of identified arrangements of the plurality of documents (13) in the document repository (12). Each matrix is structured such that each row and each column is associated with a document (13).

Abstract: A process is provided for determining relevance using an electronic system. The process includes providing a first feature vector, providing a second feature vector, and providing an indexing parameter. A parametric family of sampling distributions are provided for the first feature vector using the indexing parameter. A parametric family of sampling distributions are also provided for the second feature vector using the indexing parameter. The process further includes providing a prior distribution of the indexing parameter. A distribution of the indexing parameter, given the second feature vector and an event that the first feature vector is not relevant to the second feature vector, is assigned the value of the prior distribution of the indexing parameter.