Most information retrieval systems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express the weights of queries and the relevance degrees of documents. However, to improve the system-user interaction, it seems more adequate to express these lingui
Information retrieval with FROM: The fuzzy relational ontological model
โ Scribed by Rachel Pereira; Ivan Ricarte; Fernando Gomide
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 329 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
โฆ Synopsis
This paper presents FROM, the fuzzy relational ontological model, a novel approach to encode knowledge for information retrieval applications based upon a fuzzy set framework that consider more generic concepts differently from specific terms. Besides the model itself, the paper also presents a retrieval algorithm that exploits FROM features through the application of fuzzy operations that uses this knowledge to extend a user's query based on these fuzzy associations. Experimental results have shown that retrieval with FROM presented better overall performance than other fuzzy-based approaches for information retrieval.
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