Abstract
We have recently designed an extension of the XPath language which provides ranked answers to flexible queries taking profit of fuzzy variants of and, or and avg operators for XPath conditions, as well as two structural constraints, called down and deep, for which a certain degree of relevance is associated. In practice, this degree is very low for some answers weakly accomplishing with the original query, and hence, they should not be computed in order to alleviate the computational complexity of the information retrieval process. In this work we focus on the scalability of our interpreter for dealing with massive XML files by making use of its ability for prematurely disregarding those computations leading to non significant solutions (i.e., with a poor degree of relevance according the preferences expressed by users when using the new command FILTER). Since our proposal has been implemented with a fuzzy logic language, here we exploit the high expressive resources of this declarative paradigm for performing “dynamic thresholding” in a very natural and efficient way, thus connecting with the so-called top-k answering problem, which is very well-known in the fuzzy logic and soft computing arena.
Keywords
- Information Retrieval Systems
- Fuzzy XPath
- Information Filtering Systems
- Fuzzy Filtering & Thresholding
- Fuzzy Logic Programming
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Almendros-Jiménez, J.M., Luna Tedesqui, A., Moreno, G. (2014). Dynamic Filtering of Ranked Answers When Evaluating Fuzzy XPath Queries. In: Cornelis, C., Kryszkiewicz, M., Ślȩzak, D., Ruiz, E.M., Bello, R., Shang, L. (eds) Rough Sets and Current Trends in Computing. RSCTC 2014. Lecture Notes in Computer Science(), vol 8536. Springer, Cham. https://doi.org/10.1007/978-3-319-08644-6_33
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DOI: https://doi.org/10.1007/978-3-319-08644-6_33
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