### Table 2: Euclidean Distance Table

### Table 1 Euclidean distance matrix

### Table 1: Performance Evaluation based on Euclidean Distance

"... In PAGE 20: ...t al. 01, Dill et al. 01]. The difierences between PageRankSum and the algorithms under investigation are shown in Table1 , in terms of Euclidean distance between the rank vectors. From Table 1, we can see that the AggregateRank algorithm has the best performance: its Euclidean distance from PageRankSum is only 0.... In PAGE 20: ...t al. 01, Dill et al. 01]. The difierences between PageRankSum and the algorithms under investigation are shown in Table 1, in terms of Euclidean distance between the rank vectors. From Table1 , we can see that the AggregateRank algorithm has the best performance: its Euclidean distance from PageRankSum is only 0.0057, while the ranking results produced by the other two algorithms are farther from PageRankSum, with Euclidean distances of 0.... ..."

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### Table 2 Mutual Squared Euclidean Distance Cluster

"... In PAGE 7: ...(total number of components), SED (Squared Euclidean Distance), and eigenvalue of each component are also shown in Table 1. Table2 indicates mutual SED between clusters. As shown in Table 2, the SED of Cluster III was the smallest, in other words, Cluster III was the closest to the origin among classified 6 clusters.... In PAGE 9: ...3.3 Discussion Table2 shows that Cluster III represents public comments the most, while Cluster I the second-most. In comparison with Clusters I and III, the other clusters were relatively outside the mainstream of public opinions.... In PAGE 24: ..., 2004). List of Tables Table 1 Keyword cluster classification (N=151) Table2 Mutual Squared Euclidean Distance of clusters Table 3 Keyword classification of subcluster of cluster I (N=51)... ..."

### Table 1: Euclidean distance with early abandonment 1

2005

"... In PAGE 2: ... Early Abandon: During the computation of the Euclidean distance, if we note that the current sum of the squared differences between each pair of corresponding data points exceeds r2, we can stop the calculation, secure in the knowledge that the exact Euclidean distance had we calculated it, would exceed r. Figure 2: Illustration of early abandoning While the idea of early abandoning is fairly obvious and intuitive [7], it is so critical to our work we illustrate it in Figure 2 and provide pseudocode in Table1 . We call the distance computation of each pair of corresponding data points a step, and we use num_steps to measure the utility of early abandonment.... In PAGE 6: ...2 A Final Optimization There is one simple additional optimization that we can do to speed up Atomic Wedgie. Recall that in both Table1 and Table 2 when we explained early abandoning we assumed that the distance calculation proceeded from left to right (cf. Figure 2).... ..."

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### Table 5. The average Euclidean distances between the archiphonemes.

"... In PAGE 5: ...45 /v/ 1.56 As with the consonants, the correlations between the vowels were also analyzed by calculating the av- erage distances of each vowel to all other vowels (see Table5 ). The average distances in Table 5 show that /e/ correlates most with the other phonemes and is therefore more error prone in a noisy environment.... In PAGE 9: ... Particu- larly /e/ tended to include errors. The reason for this is again the smallest average distance between /e/ and the other vowels (see Table5 ), which renders it more sensible to the noise than the other vowels. Albeit errors of single phonemes are rather im- probable, the phoneme networks yield more phoneme errors than the errors of single phonemes would sug- gest.... ..."

### Table 9: MBI matrix for squared Euclidean distance.

2004

"... In PAGE 58: ... Using Table 8, we can exactly compute each of the relevant conditional expectations, which requires O(mn) operations. Though we do not explicitly compute it, the MBI matrix Z (shown in Table9 ) can be expressed in terms of the row clustering R, column clustering C and these conditional expectations for any co-clustering basis. 2.... ..."

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### Table 2 Reduction of necessary Euclidean distance calculations

1993

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### Table 2 Reduction of necessary Euclidean distance calculations

1993

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### TABLE I EUCLIDEAN DISTANCES FOR CPM AND CECPM SCHEMES.

2003

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