Kevin Knight [5]Kevin M. Knight [1]
  1. Measuring inconsistency.Kevin Knight - 2002 - Journal of Philosophical Logic 31 (1):77-98.
    I provide a method of measuring the inconsistency of a set of sentences from 1-consistency, corresponding to complete consistency, to 0-consistency, corresponding to the explicit presence of a contradiction. Using this notion to analyze the lottery paradox, one can see that the set of sentences capturing the paradox has a high degree of consistency (assuming, of course, a sufficiently large lottery). The measure of consistency, however, is not limited to paradoxes. I also provide results for general sets of sentences.
    Direct download (6 more)  
    Export citation  
    Bookmark   23 citations  
  2.  10
    Summarization beyond sentence extraction: A probabilistic approach to sentence compression.Kevin Knight & Daniel Marcu - 2002 - Artificial Intelligence 139 (1):91-107.
  3.  39
    Two information measures for inconsistent sets.Kevin M. Knight - 2003 - Journal of Logic, Language and Information 12 (2):227-248.
    I present two measures of information for both consistentand inconsistent sets of sentences in a finite language ofpropositional logic. The measures of information are based onmeasures of inconsistency developed in Knight (2002).Relative information measures are then provided corresponding to thetwo information measures.
    Direct download (4 more)  
    Export citation  
    Bookmark   3 citations  
  4.  4
    Discovering the linear writing order of a two-dimensional ancient hieroglyphic script.Shou de Lin & Kevin Knight - 2006 - Artificial Intelligence 170 (4-5):409-421.
    Direct download (2 more)  
    Export citation  
  5.  6
    Fast and optimal decoding for machine translation.Ulrich Germann, Michael Jahr, Kevin Knight, Daniel Marcu & Kenji Yamada - 2004 - Artificial Intelligence 154 (1-2):127-143.
    Direct download (2 more)  
    Export citation  
  6.  13
    Probabilistic Entailment and a Non-Probabilistic Logic.Kevin Knight - 2003 - Logic Journal of the IGPL 11 (3):353-365.
    In this paper we present a probabilistic notion of entailment for finite sets of premises, which has classical entailment as a special case, and show that it is well defined; i.e., that the problem of whether a sentence is entailed by a set of premises is computable. Further we present a natural deductive system and prove that it is the strongest deductive system possible without referring to probabilities.
    Direct download  
    Export citation  
    Bookmark   1 citation