Sentence packaging is an important task in natural language text generation which could be treated as a particular kind of a community detection problem. We propose an approach based on genetic algorithm and predictive machine learning models to advance it. The approach allows handling large ontological and semantic structures in a form of a graph to produce well-formed sentences. The results of experiments showed that the genetic algorithm optimizing the modularity measure gives comparable results to ones achieved by a traditional community detection algorithm and outperforms it on a collection of relatively short texts. The design of an approach allows for further introducing linguistic characteristics into a fitness function that gives it a high potential to increase the quality of detected packages while taking into account the specificity of the domain.
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Devyatkin D., Isakov V., Shvets A. Genetic algorithm based sentence packaging in natural language text generation // IOP Conference Series: Materials Science and Engineering. – IOP Publishing, 2019. – Vol. 537. – №. 4. – p. 042003.