Pirkola, A.; Puolamäki, D.; Järvelin, K.: Applying query structuring in cross-language retrieval (2003)
0.00
8.63584E-4 = product of:
0.003454336 = sum of:
0.003454336 = product of:
0.010363008 = sum of:
0.010363008 = weight(_text_:a in 1074) [ClassicSimilarity], result of:
0.010363008 = score(doc=1074,freq=12.0), product of:
0.055348642 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.04800207 = queryNorm
0.18723148 = fieldWeight in 1074, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.046875 = fieldNorm(doc=1074)
0.33333334 = coord(1/3)
0.25 = coord(1/4)
- Abstract
- We will explore various ways to apply query structuring in cross-language information retrieval. In the first test, English queries were translated into Finnish using an electronic dictionary, and were run in a Finnish newspaper database of 55,000 articles. Queries were structured by combining the Finnish translation equivalents of the same English query key using the syn-operator of the InQuery retrieval system. Structured queries performed markedly better than unstructured queries. Second, the effects of compound-based structuring using a proximity operator for the translation equivalents of query language compound components were tested. The method was not useful in syn-based queries but resulted in decrease in retrieval effectiveness. Proper names are often non-identical spelling variants in different languages. This allows n-gram based translation of names not included in a dictionary. In the third test, a query structuring method where the Boolean and-operator was used to assign more weight to keys translated through n-gram matching gave good results.
- Type
- a
