Herrera-Viedma, E.; Cordón, O.; Herrera, J.C.; Luqe, M.: ¬An IRS based on multi-granular lnguistic information (2003)
0.01
0.011183805 = product of:
0.055919025 = sum of:
0.055919025 = weight(_text_:system in 2740) [ClassicSimilarity], result of:
0.055919025 = score(doc=2740,freq=8.0), product of:
0.13391352 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.04251826 = queryNorm
0.41757566 = fieldWeight in 2740, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.046875 = fieldNorm(doc=2740)
0.2 = coord(1/5)
- Abstract
- An information retrieval system (IRS) based on fuzzy multi-granular linguistic information is proposed. The system has an evaluation method to process multi-granular linguistic information, in such a way that the inputs to the IRS are represented in a different linguistic domain than the outputs. The system accepts Boolean queries whose terms are weighted by means of the ordinal linguistic values represented by the linguistic variable "Importance" assessed an a label set S. The system evaluates the weighted queries according to a threshold semantic and obtains the linguistic retrieval status values (RSV) of documents represented by a linguistic variable "Relevance" expressed in a different label set S'. The advantage of this linguistic IRS with respect to others is that the use of the multi-granular linguistic information facilitates and improves the IRS-user interaction
