Since network resources are usually limited, the ability to carry out resource reservation in advance, as well as efficient dynamic multicasting when destination nodes can join and leave the group during the communication period, are essential in all distributed multi-party applications. Total or partial re-routing of a multicast tree for dynamic multicast groups can optimize the tree cost to some extent but they are complex. Furthermore, optimal multicast routing has been proved to be an NP-complete problem. In this paper, we propose an efficient dynamic multicast routing algorithm, which optimizes the total cost of the Steiner tree over the whole session period in an advance resource reservation environment, where information about the resource reservation (i.e. leaving times of participants at the time of joining) are available. The efficiency of our algorithm compared to other existing algorithms is shown by various simulation results.

Dynamic multicast routing in advance resource reservation environment

An automatic summarization system for local assembly minutes is described. Our system is unique in the following two points: First, the completeness that puts emphasis on the readability of the generated summary is realized. Secondly, the preference that prioritizes the selection based on the viewpoint on the content of the summary is considered. Our system has a t wo-level structure that brings about the property of "anytime algorithm": The neural network in the lower layer recollects important sentences based on the frequency of the words in the text. Then, based on the snapshot of the neural network, the summary gnerator in the upper layer extracts a cluster of sentences around the important sentences, with the prioritization by the user's preferred viewpoint. The effectiveness of our method is demonstrated using the actual minutes of a prefecture in Japan.

A neural network-based automatic summarization for the minutes of local assemblies

A method for analyzing a thought system of a subject consisting of at least one individual is disclosed. The analyzing method comprising the steps of: obtaining a plurality of items perceived by the subject; obtaining relationship information of all possible item pairs based on perception of the subject with respect to relationship between two items of each of said all possible item pairs; generating a relation matrix of the plurality of items based on the relationship information of each of the items with respect to the all other items; transforming the relation matrix to a display matrix projected on a representation space having dimensions lower than the number of the items and reflecting a relationship between the items perceived by the subject; and displaying the items on the representation space according to the display matrix such that the items are plotted on respective positions in the representation. An apparatus for analyzing a thought system of a subject which is adapted to perform the present analyzing method is also disclosed.

Method and apparatus for analyzing thought system

We have developed the Connectionist Inference Mechanism (CIM) to serve as a connectionist alternative to the symbolic inference module of P. Buchheit's (1991) Informational Network For A Natural Thinking (INFANT) System. CIM consists of several modules working together, including memory, neural networks, and a binding set. Its main task is to perform inference generation with the capability of variable binding. CIM is essentially a hybrid cognitive model that combines the advantages of a symbolic approach, local representation, and parallel distributed processing. It can be shown that each approach complements and supports the others.

M.W. Evens

Papers

A connectionist inference mechanism for a natural language understanding system