DocumentCode :
1711947
Title :
Similarity or inference for assessing relevance in information retrieval
Author :
Cross, Valerie V.
Author_Institution :
Dept. of Comput. Sci. & Eng., South Carolina Univ., Columbia, SC, USA
Volume :
3
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
1287
Lastpage :
1290
Abstract :
The primary objective of an information retrieval system is to provide the user with relevant documents given the user´s query. Numerous approaches to determining a document´s relevance have been proposed based on the underlying retrieval model. In the paper, similarity-based and inference-based IR models are examined. A fuzzy information retrieval model is presented such that assessing document relevancy is based on the user´s interpretation of the query term weights. The close relationship between the similarity-based and inference-based IR models is investigated in the context of the fuzzy information retrieval model
Keywords :
Boolean algebra; fuzzy logic; fuzzy set theory; inference mechanisms; relevance feedback; document relevance; fuzzy information retrieval model; inference-based models; query term weights; relevance assessment; relevant documents; retrieval model; similarity-based models; Computer science; Context modeling; Fuzzy set theory; Information retrieval; Logic; Proposals; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-7293-X
Type :
conf
DOI :
10.1109/FUZZ.2001.1008894
Filename :
1008894
Link To Document :
بازگشت