nep-cmp New Economics Papers
on Computational Economics
Issue of 2005‒09‒17
two papers chosen by
Stan Miles
York University

  1. An Efficient Algorithm for Frequent Pattern Mining for Real-Time Business Intelligence Analytics in Dense Datasets By Rajanish Dass
  2. Knowledge Representation and Search Processes - a contribution to the microeconomics of invention and innovation By Frank Beckenbach

  1. By: Rajanish Dass
    Abstract: Finding frequent patterns from databases has been the most time consuming process in data mining tasks, like association rule mining. Frequent pattern mining in real-time is of increasing thrust in many business applications such as e-commerce, recommender systems, and supply-chain management and group decision support systems, to name a few. A plethora of efficient algorithms have been proposed till date, among which, vertical mining algorithms have been found to be very effective, usually outperforming the horizontal ones. However, with dense datasets, the performances of these algorithms significantly degrade. Moreover, these algorithms are not suited to respond to the real-time need. In this paper, we describe BDFS(b)-diff-sets, an algorithm to perform real-time frequent pattern mining using diff-sets and limited computing resources. Empirical evaluations show that our algorithm can make a fair estimation of the probable frequent patterns and reaches some of the longest frequent patterns much faster than the existing algorithms.
    Date: 2005–08–17
  2. By: Frank Beckenbach (Department of Economics, University of Kassel)
    Abstract: Novelty creating processes have been mainly analysed in a 'post-revelation' situation and by taking a meso (or even macro) level perspective. One reason for this might be a methodological caveat according to which firstly the novelty creating process (henceforth: ncp) is totally conjectural without anything to generalize and secondly the results of a ncp can not be anticipated leaving only room for some after-the-fact-analysis on a more or less aggregated level. Without denying these assumptions the following considerations assume that it is worthwhile to analyse the ncp from a microeconomic perspective including 'prerevelation' situations. The subject matter of such an analysis is constituted by the following components: - the triggering conditions for ncps, - the constraints for ncps, - the expectations of agents/agencies promoting ncps, - the heuristics for ncps and finally - the processing of the ncps themselves. In this article I will deal with these topics by proceeding in the following manner: (1) I discuss the shortcomings of the usual analysis of ncp in evolutionary economics and pick up some hints of the cognitive sciences to overcome these conceptual shortcomings (section II). (2) I try to combine stylised facts of the microeconomic analysis of ncps with conceptual ideas about a cognitive architecture of agents and knowledge networks for getting a modelling framework. (3) I will present some preliminary simulation results for parts of this simulation model (section III).
    Date: 2005–08

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