### Table 5. Adjacency pairs

"... In PAGE 24: ... Other pairs include greeting-greeting, goodbye-goodbye, confirmation-confirmation. Table5 displays the number of first parts in each type of conversation, broken down into questions, tag questions and other. In push-to-talk, the majority of turns (81.... ..."

### Table 3: E#0Bect of di#0Berent document term weighting functions: single terms and adjacent pairs

1993

"... In PAGE 5: ... This may be a consequence of the greater varia- tion in document lengths found in the large databases. Table3 compares the more elaborate term weighting functions with the standard w #281#29 weighting and with a baseline coordination level run. Some work was done on the addition of adjacent pairs of topic terms to the queries #28see Section 2.... In PAGE 5: ...f topic terms to the queries #28see Section 2.5#29. Anum- ber of runs were done, using several di#0Berentways of ad- justing the #5Cnatural quot; weights of adjacent pairs. There was little di#0Berence between them, and the results are at best only slightly better than those from single terms alone #28 Table3 #29. There was also little di#0Berence between using all adjacent pairs and using only those pairs which derive from the same sentence of the topic, with no in- tervening punctuation.... In PAGE 9: ... In the ad-hoc runs, with no qtf component, BM15 is 14#25 better than BM1 on average precision and about 9#25 better on high precision and re- call. The corresponding #0Cgures for BM11 are 51#25 and 34#25 #28 Table3 #29. For the routing runs, where a consider- able amount of relevance information had contributed to the term weights, the improvement is less, but still very signi#0Ccant#28Table 4#29.... ..."

Cited by 10

### Table 5 Five ways a region can relate to a pair of adjacent cells Relation Interpretation for region r and adjacent pair of cells (c; d)

1998

Cited by 26

### Table 5 Five ways a region can relate to a pair of adjacent cells Relation Interpretation for region r and adjacent pair of cells (c; d)

### Table 4: The binary relation \pairs of adjacent faces quot;.

"... In PAGE 6: ... As stopping criterion Sc = 1 has been choosen due to the restriction of the hypothesis language. The generalized distribution of pairs of adjacent faces can be described as follows ( Table4 ), where ni denotes the slope (n 2 fh; v; og) and the number of breakpoints (i = 3; 4; : : : ) of a face: in total exist 40,822 pairs of adjacent faces in the data, whereas 63 classes are not empty. Eight classes (bold printed) represent the 0.... In PAGE 7: ... The relative error by the use of a non-optimal distribution like Q is 182% and this error expresses the ine ciency according to the idea of the shortest description length. Analogously the pairs of adjacent faces are evaluated ( Table4 ). The information of the distri- bution P0 of the pairs of adjacent faces is IP0 = 4:37 and the... ..."

### Table 4: The binary relation \pairs of adjacent faces quot;.

"... In PAGE 6: ... As stopping criterion Sc = 1 has been choosen due to the restriction of the hypothesis language. The generalized distribution of pairs of adjacent faces can be described as follows ( Table4 ), where ni denotes the slope (n 2 fh; v; og) and the number of breakpoints (i = 3; 4; : : : ) of a face: in total exist 40,822 pairs of adjacent faces in the data, whereas 63 classes are not empty. Eight classes (bold printed) represent the 0.... In PAGE 7: ... The relative error by the use of a non-optimal distribution like Q is 182% and this error expresses the ine ciency according to the idea of the shortest description length. Analogously the pairs of adjacent faces are evaluated ( Table4 ). The information of the distri- bution P0 of the pairs of adjacent faces is IP0 = 4:37 and the... ..."

### Table 1: Numbers of adjacency pairs containing nocommunication problems (: PROBLEMS) and those containing one or more prob- lems (PROBLEMS), as a function of verification strategy.

1999

"... In PAGE 4: ...1. Table1 0: Precision and recall percentages for positive cues (single conditions), both for explicit and implicit verification. EXPLICIT IMPLICIT CONDITION precision recall precision recall a nr.... ..."

Cited by 15

### Table 1: Numbers of adjacency pairs containing nocommunication problems (: PROBLEMS) and those containing one or more prob- lems (PROBLEMS), as a function of verification strategy.

1999

"... In PAGE 4: ...1. Table1 0: Precision and recall percentages for positive cues (single conditions), both for explicit and implicit verification. EXPLICIT IMPLICIT CONDITION precision recall precision recall a nr.... ..."

Cited by 15

### Table 1: Numbers of adjacency pairs containing nocommunication problems (: PROBLEMS) and those containing one or more prob- lems (PROBLEMS), as a function of verification strategy.

1999

"... In PAGE 4: ...1. Table1 0: Precision and recall percentages for positive cues (single conditions), both for explicit and implicit verification. EXPLICIT IMPLICIT CONDITION precision recall precision recall a nr.... ..."

Cited by 15

1999

Cited by 15