Abstract: Exemplary embodiments include a method for re-ordering and visualizing a matrix in the presence of a data hierarchy stored on a computer system, the method including receiving a matrix, A, in the computer system, the matrix A having rows and columns, reordering the matrix A so that groups of related rows and columns are brought in adjacent matrix positions, wherein reordering the matrix A obeys constraints imposed by the data hierarchy on at least one of the rows and the columns and reordering the hierarchy on at least one of the rows and columns, wherein affinities in the data hierarchy are extracted by the reordering of the data hierarchy.

Abstract: A method, system and computer product for visualizing affinities between objects. The method includes the steps of: forming a representation of a minimum spanning tree where the minimum spanning tree connects the plurality of objects based on a pairwise distance between the plurality of objects; forming a hierarchical cluster of the plurality of objects where the hierarchical cluster includes a level; agglomerating the plurality of objects based on the pairwise distance; displaying a view of the representation of the minimum spanning tree in a graphical user interface; receiving a user selection of a parameter containing a hierarchical level; and identifying, in the view, a target cluster that corresponds to the hierarchical level; where at least one of the steps is carried out using a computer device so that affinities between the plurality of objects are visualized.

Abstract: Method for dynamically allocating a cost to an e-mail that a first user of a transmission network such as the Internet network or an Intranet network who is a member of a group, wants to forward to a second user of the transmission network who is also a member of the group. The method comprising the steps of forwarding by the first user the e-mail to a market engine in charge of allocating a cost to the e-mail, determining by the market engine the cost of the e-mail based upon intrinsic and extrinsic criteria, submitting the cost of the e-mail to the first user for agreement, forwarding by the market engine the e-mail to the second user, and updating a credit account associated with the first user.

Abstract: This invention provides techniques, systems and apparatus for assessing risk associated with a project or a portfolio of projects. An example embodiment having a processor and a memory, includes storing operational values which corresponds to a different project. Each operational value is representative of a project operational parameter. A risk vector is generated for each project based on the set of operational parameters. The risk vectors are partitioned into groups of similar risk vectors having a set of membership rules. Probabilities that a new project belongs to respective groups are generated. A risk value indicative of the risk associated with the new project is generated based on the probabilities generated. In some embodiments, the technique also assesses portfolio risk and utilizes an optimization algorithm to estimate acceptable or desirable margins to charge for each project in a portfolio of projects.

Abstract: The invention is directed to a method for assigning to a set of products a set of corresponding continuous demand densities. In a conversion step for each product its demand time series is converted into a discrete demand density. In a normalization step the discrete demand densities are transformed into normalized discrete demand densities. In a clustering step each of the normalized discrete demand densities is assigned to a cluster and for each cluster a cluster-representative discrete density is determined. In a selection step for each cluster-representative discrete density out of a predetermined set of continuous model densities a cluster-representative continuous density is selected. In a parameter-determination step for each product for its cluster-representative continuous density product-individual density parameters are determined under use of which for each product a continuous density is determined.

Abstract: The invention is directed to a method for assigning to a set of products a set of corresponding continuous demand densities. In a conversion step for each product its demand time series is converted into a discrete demand density. In a normalization step the discrete demand densities are transformed into normalized discrete demand densities. In a clustering step each of the normalized discrete demand densities is assigned to a cluster and for each cluster a cluster-representative discrete density is determined. In a selection step for each cluster-representative discrete density out of a predetermined set of continuous model densities a cluster-representative continuous density is selected. In a parameter-determination step for each product for its cluster-representative continuous density product-individual density parameters are determined under use of which for each product a continuous density is determined.

Abstract: Method for dynamically allocating a cost to an e-mail that a first user of a transmission network such as the Internet network or an Intranet network who is a member of a group, wants to forward to a second user of the transmission network who is also a member of the group. The method comprising the steps of forwarding by the first user the e-mail to a market engine in charge of allocating a cost to the e-mail, determining by the market engine the cost of the e-mail based upon intrinsic and extrinsic criteria, submitting the cost of the e-mail to the first user for agreement, forwarding by the market engine the e-mail to the second user, and updating a credit account associated with the first user.

Abstract: This invention provides techniques, systems and apparatus for assessing risk associated with a project or a portfolio of projects. An example embodiment having a processor and a memory, includes storing operational values which corresponds to a different project. Each operational value is representative of a project operational parameter. A risk vector is generated for each project based on the set of operational parameters. The risk vectors are partitioned into groups of similar risk vectors having a set of membership rules. Probabilities that a new project belongs to respective groups are generated. A risk value indicative of the risk associated with the new project is generated based on the probabilities generated. In some embodiments, the technique also assesses portfolio risk and utilizes an optimization algorithm to estimate acceptable or desirable margins to charge for each project in a portfolio of projects.