Paper Review Form
			      for
		Data Mining and Knowledge Discovery 
 	   Special Issue on E-Commerce and Data Mining
        http://robotics.stanford.edu/~ronnyk/ecommerce-dm/

Title:							Code:
Author(s):						Date:

______________________________________________________________________
APPROPRIATENESS:  Is this paper appropriate for this special issue
                  on e-commerce and data mining?
______________________________________________________________________


______________________________________________________________________
CONTRIBUTION: What contribution is made by this paper?  Assess the
              novelty of the contribution.  Assess the generality of
              the contribution.  How significant is the contribution
              from an applications perspective?  From a research
              perspective?  Will it stimulate future research?  Does
              it provide useful knowledge for future applications?

              Contributions include: new ways or approaches to use
	      existing data mining technology for e-commerce, analyses
	      of simplifying assumptions commonly made in KDD
	      literature that cannot be made in applications,
	      comparisons of methods for addressing such simplifying
	      assumptions, modifications of existing methods to
	      address applications issues, methods for other aspects
	      of the knowledge discovery process, analysis of why
	      existing methods fail for a particular application,
	      analysis of the overall process of knowledge discovery
	      methods, etc.
______________________________________________________________________


______________________________________________________________________
DEFINITION & MOTIVATION:

      Is the application task clearly defined? Is the need for knowledge
      discovery motivated well?  Is there evidence of significant ROI
      or important new capabilities (as much as possible)?  Are
      existing or alternative methods discussed.  Are the important
      facets of the task identified in such a way that the results
      will generalize to similar problems?  Is a class of problems
      with similar characteristics defined?  Are the evaluation
      criteria well motivated from the perspective of the application
      task (i.e., do they reflect the target task)?  

      Is the knowledge discovery process well defined?  Does the paper
      focus on the entire knowledge discovery process, or a particular
      segment? (Segments are fine, but this fact must be made clear.)
      
      Are the methods clearly defined?  Is their use motivated well?
      Is their choice (over other methods) well justified?  Are the
      methods specific to this problem, or will they generalize?
      Do the authors mention generalizations either to other problems
      in e-commerce or to other problems outside e-commerce?
      Are the limitations on generalization enumerated?  Are the methods
      technically sound?
______________________________________________________________________


______________________________________________________________________
SUPPORT: How do the authors provide support for the paper's
         contribution (e.g., empirical evaluation, theoretical
         justification, demonstration, survey of the literature,
         etc.).  Do they provide sufficient support for their claims?
         Is the argument technically & logically sound?
______________________________________________________________________


______________________________________________________________________
DISCUSSION: Does the paper provide an adequate discussion of related
            work?  Does it describe similarities, differences, and
            progress?  Does the paper discuss the implications of its
            contribution? Does the paper argue for a new research
            direction?  If so, does the paper provide an adequate
            description of the current state of research in this
            direction? Does the paper identify the limitations of its
            contribution and the simplifying assumptions made?  Does
            the paper discuss lessons learned in applying data mining
            techniques that are of general interest?
            
            Does the paper discuss non-technical issues in applying
            the technology that may be generally useful?
______________________________________________________________________



______________________________________________________________________
GENERAL: Is the paper well-organized and well-written?  Does it use
         standard terminology?  Has the author provided sufficient
         background?  Are an appropriate number of informative figures
         included?  Are results presented clearly?  Does the abstract
         and title adequately reflect the contents?

         Does anything need to be added or deleted?
______________________________________________________________________


Recommendation:

	o accept
	o accept after minor revisions
	o encourage resubmission to the journal after
	  a major revision (not for special issue)
	o encourage submission to the journal: ______________
	o reject