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Tables Query Query

in TINTIN: A System for Retrieval in Text Tables
by Pallavi Pyreddy, W. Bruce Croft 1997
Cited by 23

Table 4. Average values for key variables used for clustering of query data (corresponding to cluster groups in Table 3), and one comparative variable not used in clustering (Freq of URL 1)

in unknown title
by unknown authors
"... In PAGE 6: ... Table4 . Average values for key variables used for clustering of query data (corresponding to cluster groups in Table 3), and one comparative variable not used in clustering (Freq of URL 1) Average values (for each cluster) Confidence Document Cluster* Hold time Ranking Freq.... In PAGE 7: ... Table4 . Average values for key variables used for clustering of query data (corresponding to cluster groups in Table 3), and one comparative variable not used in clustering (Freq of URL 1) Average values (for each cluster) Confidence Document Cluster* Hold time Ranking Freq.... In PAGE 8: ... Table4 . Average values for key variables used for clustering of query data (corresponding to cluster groups in Table 3), and one comparative variable not used in clustering (Freq of URL 1) Average values (for each cluster) Confidence Document Cluster* Hold time Ranking Freq.... In PAGE 9: ... Table4 . Average values for key variables used for clustering of query data (corresponding to cluster groups in Table 3), and one comparative variable not used in clustering (Freq of URL 1) Average values (for each cluster) Confidence Document Cluster* Hold time Ranking Freq.... In PAGE 10: ... Table4 . Average values for key variables used for clustering of query data (corresponding to cluster groups in Table 3), and one comparative variable not used in clustering (Freq of URL 1) Average values (for each cluster) Confidence Document Cluster* Hold time Ranking Freq.... ..."

Table 1. Types of Questions Asked by Subject Subject of Request Number of Queries Math 40 Social Studies/History/Civics 9

in unknown title
by unknown authors 2005
Cited by 3

Table 2. Queries evaluated in the experiment. Query Query

in Re-ranking Search Results based on Perturbation of Concept-Association Graphs
by Gaurav Chandalia, Rohini Srihari
"... In PAGE 4: ... Table2 shows the queries that we have evaluated and table 3 gives details of the number of relevant docu- ments in the query and the number of relevant docu- ments that were retrieved in the baseline run. We have used the standard TREC evaluation code to evaluate the results3.... In PAGE 5: ... We have described the ideal scenarios above; there can be sev- eral others but they can be explained as one or more variations/combinations of the ideal scenarios. Figure 2 shows the precision of each of the queries in Table2 when we ran the algorithm from Section 5.2 as stated.... ..."

Table 1: Data structure comparison for range searching in milliseconds N [0, log N1/2) [log N1/2, log N) [log N, log N2)

in An Investigation of Multi-Level K-Ranges
by Sean Falconer And, Sean M. Falconer, Bradford G. Nickerson
"... In PAGE 18: ...2.1 Range Search Test Table1 lists our results from k = 2 up to and including k = 8 for searching using a naive approach (linear bruteforce search), multi-level k-ranges, and a R*tree [2, 6]. The first column for each query window size represents the average search time, TNAIV E, for the naive approach.... ..."

Table IX. Precision at Different Document Ranks using the CORI and Semisupervised Learning Approaches to Merging Retrieval Results. INQUERY Search Engine

in A Semisupervised Learning Method to Merge Search Engine Results
by Luo Si, Jamie Callan 2003
Cited by 21

Table 2: The computed clusters and the associated categories

in Online at: www.jus.org.uk A Smart Query Formulation for an Efficient Web Search
by Vincenzo Loia, Sabrina Senatore 2007
"... In PAGE 11: ... In general, the clustering performance presents interesting results: the computed values in terms of recall and precision are rather accurate for the most of experiments. Table2 shows the main categories elicited by this experimentation: according to the topics of terms in the reference set, a pertinent category is associated. Furthermore, for each category, the more relevant sample of documents associated to the flrst three page links of returned list is shown.... ..."

Table Queries

in Abstract Data Analysis and Mining in the Life Sciences
by Nam Huyn

Table III. Precision at Different Document Ranks using the CORI and Semisupervised Learning Approaches to Merging Retrieval Results. INQUERY and Language Model Search Engines Trec123 Testbed Trec4 kmeans Testbed Document

in A Semisupervised Learning Method to Merge Search Engine Results
by Luo Si, Jamie Callan 2003
Cited by 21

Table X. Precision at Different Document Ranks using the CORI and Semisupervised Learning Approaches to Merging Retrieval Results. INQUERY Search Engine Trec123 Testbed Trec4 kmeans Testbed

in A Semisupervised Learning Method to Merge Search Engine Results
by Luo Si, Jamie Callan 2003
Cited by 21
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