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Table 1: Number of Membership Queries Scenario
2003
"... In PAGE 9: ... S1 1 physical device (A), AI = fA quot;; A #g, AO = finitiatedA; clearedA; [hookswitchA]g. S2 2 physical devices (A; B), AI = fA quot;; A #; B quot;; B #g, AO = finitiatedfA;Bg; clearedfA;Bg; [hookswitchfA;Bg]g: S3 3 physical devices (A; B; C), AI = fA quot;; A #; B quot;; B #; C quot;; C #; g, AO = finitiatedfA;B;Cg; clearedfA;B;Cg; [hookswitchfA;B;Cg]g: S4 3 physical devices (A; B; C), AI = fA quot;; A #; A ! B; B quot;; B #; C quot;; C #g, AO = finitiatedfA;B;Cg; clearedfA;B;Cg; originatedA; establishedBg: Table1 lists in the flrst two columns the number of states of the model resulting from the learning pro- cess and the number of membership queries L* would need to learn the model. Roughly, the number of mem- bership queries is polynomial (between quadratic and cubic) in the number of states.... ..."
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Table A: The 57 studied queries and their corresponding scenarios
2005
Cited by 3
Table 2. Scenarios for organizer queries
"... In PAGE 4: ...sequentially, and that which are optimizable using our technique. The various combination (scenarios) of organizer queries and their naming schemes are shown in Table2 . For instance, S12 indicates that P1 is sequentially processed along with P2.... ..."
Table 1: Matrix of scenarios, queries and languages used in experiment Scenario A Scenario B Scenario C (control group)
2003
"... In PAGE 2: ... The ranked lists were presented to the participants, varied by order and language (cf. Table1 ) in a simulated search interface. - System.... ..."
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Table 1: The spatial relations, criteria and example query scenarios associated with different spatial filters. Filter Spatial
Table 3. Scenarios for TPC-H queries
"... In PAGE 4: ... For instance, S12 indicates that P1 is sequentially processed along with P2. The combination scenarios for TPC-H queries are shown in Table3 . The combinations shown in the above tables are the prominent ones and the behavior of other combinations are very similar to these, hence, they are not included in this paper.... ..."
Table 1: Example Keyword Queries and Corresponding Search Scenarios
"... In PAGE 6: ...ocument always has a score of a 100%. This allows us to apply certain thresholds to the similarity scores. Based on the user apos;s intent for the query and the search results, we calculated the precision and recall metrics for our keyword searches at each 10 point interval between similarity thresholds of 0% to 100%. Table1 displays a few examples of our keyword queries and search scenarios. ... In PAGE 7: ... Figure 4, shows the average precision and recall of the enhanced queries in comparison with simple queries. As indicated in Table1 , simple queries can contain a single keyword, two keywords, or three keywords. Figure 4: Avg.... ..."
Table 1: Example Keyword Queries and Corresponding Search Scenarios
2004
"... In PAGE 6: ...idf) weight is computed for each term in the document collection using the global dictionary of the concept hierarchy. As depicted in Table1 , our keyword queries are used to run a number of search scenarios. The first set of keyword queries contain only one term and include the following: bat, bug, hardware, mouse,andpython.... ..."
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Table 1. Example Keyword Queries and Corresponding Search Scenarios #of
2004
"... In PAGE 8: ... Table 2. User Interests and Corresponding User Profiles User Profiles User Interest Set 1 buying a baseball bat Set 1 home hardware and tools Set 1 information about a pet python Set 2 information on bat as a mammal Set 2 upgrading computer hardware Set 2 Python programming language As depicted in Table1 , our keyword queries are used to run a number of search scenarios. The first set of keyword queries contain only one term and include the following: bat, bug, hardware, mouse,andpython.... ..."
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