Calculating distances for dissimilar strings: The shortest path formulation revisited

Fast detection of string differences is a prerequisite for string clustering problems. An example of such a problem is the identification of duplicate information in the data cleansing stage of the data mining process. The relevant algorithms allow the application of large-scale clustering techniques in order to create clusters of similar strings. The vast majority of comparisons, in such cases, is between very dissimilar strings, therefore methods that perform better at detecting large differences are preferable. This paper presents approaches which comply with this requirement, based on reformulation of the underlying shortest path problem. It is believed that such methods can lead to a family of new algorithms. An upper bound algorithm is presented, as an example, which produces promising results.     

The Process Allocation Problem: a Survey of the Application of Graph-Theoretic and Integer Programming Approaches

The Process Allocation Problem, which consists of allocating a number of processes to a network of processors with the objective of minimizing the sum of communication (between processes residing on different processors) and execution costs, is presented and the relevant literature reviewed. Solution procedures employing graph-theoretic and mathematical programming methods are critically examined. Some heuristic algorithms are also presented.     

Optimum Allocation of Processes in a Distributed Environment: A Process-to-Process Approach

The process allocation problem (PAP) concerned with the assignment of a number of communicating processes to a certain number (not known a priori) of identical processors in a telecommunications environment is examined. The objective is to minimize the total message-passing between processes residing on different processors subject to constraints on the processing power and storage capacity (code-, data-storage and occupancy) of the processors. Constraints imposed on the co-location of certain processes on the same processor are also included. The problem is formulated as a 0-1 linear maximization problem, taking into account only the number of processes involved, while the number of processors required is produced automatically with the optimum solution. An implicit enumeration algorithm is developed which produces an optimum message-passing allocation. Computational results of a set of random problems which have similar characteristics to a real-world application in telecommunications are also presented.