Automatic translation of texts using volatile grammars

Cairó, Osvaldo; Guardati, Silvia

doi:10.1109/hsi.2008.4581485

Cited by 1 publication

(1 citation statement)

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“…However, big quantities of textual information require preprocessing at the stage of syntactic parsing, conceptual meaning of the phrase, semantic evaluation of the information, aggregation of the query terms and the form of its representation. There are also many tools for text processing in information retrieval [3], [4], [5] extraction [6], [7], texts summarizing [8], [9], knowledge discovery [10], similarity evaluation of the texts [11], categorization [12] and machine translation [13]. They all stimulate the need for more precise and general solutions when the tools have some technical limitations.…”

Section: Introductionmentioning

confidence: 99%

Context-sensitive text mining with fitness leveling Genetic Algorithm

Huk

Kwiatkowski

Konieczny

et al. 2015

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)

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Contextual processing is a great challenge for information retrieval study -the most approved techniques include scanning content of HTML web pages, user supported metadata analysis, automatic inference grounded on knowledge base, or content-oriented digital documents analysis. We propose a meta-heuristic by making use of Genetic Algorithms for Contextual Search (GACS) built on genetic programming (GP) and custom fitness leveling function to optimize contextual queries in exact search that represents unstructured phrases generated by the user. Our findings show that the queries built with GACS can significantly optimize the retrieval process.

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