Callan, J.: Distributed information retrieval (2000)
0.00
5.6391995E-4 = product of:
0.008458799 = sum of:
0.008458799 = product of:
0.016917598 = sum of:
0.016917598 = weight(_text_:information in 31) [ClassicSimilarity], result of:
0.016917598 = score(doc=31,freq=12.0), product of:
0.050870337 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.028978055 = queryNorm
0.3325631 = fieldWeight in 31, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0546875 = fieldNorm(doc=31)
0.5 = coord(1/2)
0.06666667 = coord(1/15)
- Abstract
- A multi-database model of distributed information retrieval is presented, in which people are assumed to have access to many searchable text databases. In such an environment, full-text information retrieval consists of discovering database contents, ranking databases by their expected ability to satisfy the query, searching a small number of databases, and merging results returned by different databases. This paper presents algorithms for each task. It also discusses how to reorganize conventional test collections into multi-database testbeds, and evaluation methodologies for multi-database experiments. A broad and diverse group of experimental results is presented to demonstrate that the algorithms are effective, efficient, robust, and scalable
- Series
- The Kluwer international series on information retrieval; 7
- Source
- Advances in information retrieval: Recent research from the Center for Intelligent Information Retrieval. Ed.: W.B. Croft
