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Table 2: Mean Typicality Ratings by Item Type from Experiment 2
"... In PAGE 5: ... Results and Discussion The difference scores and intrusion effect score for each subject in Experiment 2 were determined as in Experiment 1. The mean typicality ratings for the items of interest can be found in Table2 . The first typicality rating task showed a large difference between the ratings for the consistent items and the AB inconsistent items, m = 1.... ..."
Table 1 summarizes the comparative costs of producing, and modes of reusing each of the generalizations discussed in the preceding sections. The various necessary correct- ness generalizations developed in this paper all fall within a lattice of generalizations shown in Figure 2. From this, we see that there are a variety of factors influencing the generalizations of a popi plan. These include the generality of the truth criterion used as the basis for generalization; the particular constraints on the popi plan that are
"... In PAGE 13: ... corr. O(n 3) A Table1 : Comparison between generalization algorithms. The entrees M and A in the usage field stand for reuse as macrops and reuse by adaptation, respectively The different truth criteria can be seen as providing differing biases for EBG.... ..."
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Table 1 summarizes the general criteria. Originality and abstraction will be resumed in some cases for discussing decisions on specific knowledge contributions
2006
"... In PAGE 10: ...igure 9: Excerpts of Exemplary Taxonomies ................................................................................. 60 Tables Table1 : General Criteria.... In PAGE 59: ... Table1 : General Criteria Focus on Theory and Theory Application Deciding whether to aim at a theory or not is mainly a question of feasibility. While it is difficult in general to develop a theory that satisfies the criteria outlined in 8.... ..."
Table 1. Best reported recognition results for the USPS corpus (top: general results for comparison; bottom: results related to the discussed method)
2004
Cited by 3
Tables 3,4, and 5, respectively. Figures 7, 8, and 9 depict the intervals and the basic probability assignments graphically with a generalized cumulative distribution function (gcdf). This is the probabilistic concept of cumulative distribution function generalized to Dempster-Shafer structures where the focal elements (intervals) are represented on the x-axis and the cumulative basic probability assignments on the y-axis. A discussion of the generalization of some of the ideas from the theory of random variable to the Dempster-Shafer environment is discussed in [Yager, 1986].
2002
Cited by 18
Table 5: General characteristics of the research sample by data-gathering instrument Country General research interest Key informant interviews Observations Focus group discussions (FGDs) In-depth interviews Other
"... In PAGE 41: ... The sex-health problems and broad moral/cultural context in these sites are compared. Table5 presents the variety of participant groups and venues where data ... ..."
Table 9 shows our mean average precision scores for all base runs used in the multilingual task. We did not apply decompounding to the Finnish topics. As an aside, we see that for monolingual English, the language model is particularly effective. The results for Finnish, French, and Russian are generally in line with the monolingual results discussed above, be it that the n-gramming approaches are generally more effective on the translated topics.
"... In PAGE 7: ... Table9 : Overview of MAP scores for all multilingual runs (bottom half) and of the mono- and bilingual runs used to produce them (top half).... In PAGE 7: ...o produce them (top half). Best scores are in boldface. Officially submitted runs are marked with an asterisk. Table9 also includes the run combinations submitted as official runs; recall that all these combinations are un- weighted. The additional multilingual run having two English to Russian runs for each of the indexes scored lower with an MAP of 0.... ..."
Table 3 shows results for the generalization of explana- tions from contexts to situations discussed in [20]. Without going into the details here, in this scenario the epistemic state consists of a set a201 of pairs a16a57a61
2002
"... In PAGE 4: ... The problem Explanation Existence is associated with the important task of finding an explanation for an event a110 . Similar as in other frameworks for explanations Table 1: Complexity of Explanations Problem general case binary case Explanation a184a35a185a186 -complete a184a35a185 -complete Explanation Existence a187 a185 a188 -complete a187 a185 a186 -complete a189 -Partial Explanation a190a42a191 a168 a104 a192 -complete a190a88a193 a185 a192 -complete a189 -Partial Explanation Existence a187 a185 a188 -complete a187 a185 a186 -complete Partial Explanation a190 a191 a168 a104 a192 -complete a190 a193 a185 a192 -complete Explanatory Power a194a72a190a42a191 a168 a104 a192 -complete a194a72a190 a193 a185 a192 -complete Table 2: Complexity of Explanations: Succinct Contexts Problem general case binary case Explanation a195 a185 a196 -complete a195 a185 a188 -complete Partial Explanation a195 a185 a196 -complete a195 a185 a188 -complete Table3 : Complexity of Explanations: Situations Problem general case binary case Explanation a184 a185 a186 -complete a184 a185 -complete (e.g.... ..."
Cited by 7
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