Magennis, M.: Expert rule-based query expansion (1995)
0.00
0.0020506454 = product of:
0.004101291 = sum of:
0.004101291 = product of:
0.008202582 = sum of:
0.008202582 = weight(_text_:a in 5181) [ClassicSimilarity], result of:
0.008202582 = score(doc=5181,freq=6.0), product of:
0.053105544 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046056706 = queryNorm
0.1544581 = fieldWeight in 5181, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.0546875 = fieldNorm(doc=5181)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Examines how, for term based free text retrieval, Interactive Query Expansion (IQE) provides better retrieval performance tahn Automatic Query Expansion (AQE) but the performance of IQE depends on the strategy employed by the user to select expansion terms. The aim is to build an expert query expansion system using term selection rules based on expert users' strategies. It is expected that such a system will achieve better performance for novice or inexperienced users that either AQE or IQE. The procedure is to discover expert IQE users' term selection strategies through observation and interrogation, to construct a rule based query expansion (RQE) system based on these and to compare the resulting retrieval performance with that of comparable AQE and IQE systems
- Type
- a
