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Table 12 Correlation Coe cients by Value Only for Cosine Similarity Similarity NPL LISA CISI CRAN MED CACM

in A Framework for Understanding Latent Semantic Indexing (LSI) Performance
by April Kontostathis, William M. Pottenger
"... In PAGE 13: ... In this data we observe consistent corre- lations for negative and zero values across all collections, but there are major variances in the correlations for the positive values. Table12 shows the values when the correlation coe cient is computed for selected ranges of the cosine similarity, without taking order of co-occurrence into account. Again we note strong correlations for all collections for value ranges (-.... ..."

Table 1: Perplexity results for di#0Berent models on the Cran #28predicting words condi-

in Learning from Dyadic Data
by Thomas Hofmann, Jan Puzicha, Michael I. Jordan

Table 4: Results for MedCran All and MedCisi All

in Spectral Graph Partitioning
by unknown authors
"... In PAGE 5: ... To demon- strate this, we ran the algorithm on the data sets obtained without removing even the stop words. The confusion ma- trices of Table4 show that the algorithm is able to recover the original classes despite the presence of stop words. 5.... ..."

Table 12 Correlation Coe cients by Value Only for Cosine Similarity Similarity NPL LISA CISI CRAN MED CACM

in A Framework for Understanding Latent Semantic Indexing (LSI) Performance
by April Kontostathis, William M. Pottenger
"... In PAGE 14: ... In this data we observe consistent correlations for negative and zero values across all collections, but there are major variances in the correlations for the positive values. Table12 shows the values when the correlation coe cient is computed for selected ranges of the cosine similarity, without taking order of co-occurrence into account. Again we note strong correlations for all collections for value ranges (-.... ..."

Table 7: Approximate package sizes Package Minimum

in Online Auction Web Site Simulation
by Ahmad Sharieh

Table 3: Maintaining bounded inconsistency.

in Data Consistency in Intermittently Connected Distributed Systems
by Evaggelia Pitoura, Bharat Bhargava, Ouri Wolfson 1999
"... In PAGE 12: ... As a consequence, the degree may be bounded either by limiting the number of weak writes pending commitment or by controlling the h function. In Table3 , we outline ways of maintaining d-consistency for di erent ways of de ning d. 4 A Consistency Restoration Schema After the execution of a number of weak and strict transactions, all core copies of a data item have the same value, while its quasi copies may have as many di erent values as the number of clusters.... ..."
Cited by 33

Table 1 describes the information maintained by

in Efficient Numerical Error Bounding for Replicated Network Services
by Haifeng Yu, Amin Vahdat 2000
Cited by 37

Table 1 describes the information maintained by

in Efficient Numerical Error Bounding for Replicated Network Services
by Haifeng Yu, Amin Vahdat 2000
Cited by 37

Table 4: Summary of Maintainability Results

in SOFTWARE AGENTS FOR DLNET CONTENT REVIEW: STUDY AND EXPERIMENTATION
by Seema Mitra, Dr. Saifur Rahman Co-chairman, Dr. Csaba Egyhazy Co-chairman, Seema Mitra 2006
"... In PAGE 7: ...able 3: Raw Maintainability Results............................................................................... 30 Table4 : Summary of Maintainability Results.... ..."

Table 3: Maintaining bounded inconsistency.

in Data Consistency in Intermittently Connected Distributed Systems
by Evaggelia Pitoura, Bharat Bhargava 1999
Cited by 33
Results 11 - 20 of 5,151