SP500207 OCLC Online Computer Library Center, Inc. chapter R. Thompson National Institute of Standards and Technology Donna K. Harman Num~queries: Total number of Retrieved: Relevant: Rel_ret: Trunc_ret: Recall Precis at 0.00 at 0.10 at 0.20 at 0.30 at 0.40 at 0.50 at 0.60 at 0.70 at 0.80 at 0.90 at 1.00 Average precision 11-pt Avg: Average precision 3-pt Avg: Table III 25 documents over all queries 5000 245 166 4432 ion Averages: 0.3590 0.3031 0.2118 0.1641 0.1444 0.1269 0.0946 0.0819 0.0599 0.0322 0.0292 for all points 0.1461 for 3 intermediate points (0.20, 0.50, 0.80) 0.1329 Precision Results for Eleven Levels of Recall with FASIT Indexing Num_queries: 25 Total number of documents over all queries Retrieved: 5000 Relevant: 245 Rel_ret: 164 Trunc_ret: 4382 Recall - Precision Averages: at 0.00 0.3867 at 0.10 0.3092 at 0.20 0.2369 at 0.30 0.1918 at 0.40 0.1449 at 0.50 0.1034 at 0.60 0.0816 at 0.70 0.0666 at 0.80 0.0501 at 0.90 0.0458 at 1.00 0.0337 Average precision for all points 11-pt Avg: 0.1501 Average precision for 3 intermediate points (0.20, 0.50, 0.80) 3-pt Avg: 0.1301 The higher precision scores at the lowest levels of recall are a replication of the experiments with FASIT reported in Dillon and McDonald (1983) and Burgin and Dillon (1992), and support the hypothesis that phrase indexing serves primarily as a precision enhancer. In the higher levels of recall, the effects of phrase indexing and stem indexing are essentially the same, indicating that retrieval performance is not jeopardized by the reduced document representation. We expect larger gains in precision with phrase indexing as we fine-tune our phrase-extraction algorithms. References Burgin and Dillon, M (1992). Improving Disambiguation in FASIT. 191