| S15-2154 | tree . The main idea is to apply | graph traversal | algorithms to convert a directed |
| S14-2080 | transformation approach . We use | graph traversal | algorithms to convert a directed |
| C90-2068 | nodes encountered on a particular | graph traversal | . Pollack contrasts the above |
| W13-4306 | can be exploited using simple | graph traversal | to generate the subjectivity |
| W15-0126 | depth-first and breadth-first | graph traversals | , possibly changing the edge |
| W07-1427 | Pre - viously , we wrote tedious | graph traversal | code by hand for each desired |
| W07-1501 | Similar information generated via | graph traversal | can obviously provide a wealth |
| N04-1035 | this step requires only a single | graph traversal | , it runs in linear time . Step |
| W01-0807 | simple condi - tions : compared to | graph traversal | , the evaluation of conditions |
| S14-2080 | tree . Depth-first-search We try | graph traversal | by depth-first-search starting |
| W15-0126 | further , and perform depth-first | graph traversal | . We traverse the undirected |
| S14-2081 | is based on depth-first search | graph traversal | and edge flipping . In it , we |
| W15-0126 | it is governed by the order of | graph traversal | . In both cases , some edges |
| J97-1004 | , reorganization methods , and | graph traversal | . By assembling these diverse |
| W07-1501 | application of well-established | graph traversal | and analysis algorithms to produce |
| W90-0118 | structure matching ( Hovy 1988 ) , | graph traversal | algorithms ( Paris & McKeown |
| W90-0118 | background before primary material . | Graph Traversal | . These are algorithms for selectively |
| D15-1038 | ∈ Js/r1 / ... / rkK . Writing | graph traversal | in this way immediately suggests |
| P98-2168 | allows us to substitute efficient | graph traversal | for generalised plan - ning . |
| W05-0506 | sentences , easily computed by | graph traversal | . This is similar to -LSB- Edel |
