| W02-1903 | method . In the first pass , the | indexing engine | calculates local scores of the |
| W01-1202 | homepage of Sogang University . The | indexing engine | created the 14 answer DBs ( 14 |
| W01-1202 | the same semantic category . The | indexing engine | saves the normalized term scores |
| W01-1202 | according to preference . The | indexing engine | uses the following ranking order |
| W01-1202 | including an answer candidate . The | indexing engine | gives 2 points to each content |
| W01-1202 | call the score a term score . The | indexing engine | assigns term scores to content |
| W01-1202 | engine and a searching engine . The | indexing engine | first extracts all answer candidates |
| W02-1903 | expressions . In the next stage , the | indexing engine | gives scores to content words |
| W01-1202 | ) * $ In the next stage , the | indexing engine | gives scores to content words |
| W02-1903 | dynamically changed . When the | indexing engine | decides the window size , it |
| W01-1202 | dynamically changed . When the | indexing engine | decides the window size , it |
| W02-1903 | category from documents , the | indexing engine | uses a POS tagger and a NE recognizer |
| W01-1202 | category from documents , the | indexing engine | uses a POS tagger and a NE recognizer |
| W01-1202 | gives 1 point to others . The | indexing engine | adds up the scores of the 5 features |
| W01-1202 | the above sample sentence . The | indexing engine | gives 2 points to each appositive |
| W02-1903 | it consists of two engines ; an | indexing engine | and a searching engine . 2.1 |
| W01-1202 | It consists of two engines ; an | indexing engine | and a searching engine . The |
| W01-1202 | candidate . As a result , the | indexing engine | creates 14 DB 's that correspond |
| W01-1202 | words in adjacent sentences . The | indexing engine | gives 2 points to each word that |
| A97-1049 | configurations of the same fast | indexing engine | called NameTagTm for different |
