Generating Acrostics via Paraphrasing and Heuristic Search

Benno Stein, Matthias Hagen, Christof Bräutigam
2014 International Conference on Computational Linguistics  
We consider the problem of automatically paraphrasing a text in order to find an equivalent text that contains a given acrostic. A text contains an acrostic, if the first letters of a range of consecutive lines form a word or phrase. Our approach turns this paraphrasing task into an optimization problem: we use various existing and also new paraphrasing techniques as operators applicable to intermediate versions of a text (e.g., replacing synonyms), and we search for an operator sequence with
more » ... nimum text quality loss. The experiments show that many acrostics based on common English words can be generated in less than a minute. However, we see our main contribution in the presented technology paradigm: a novel and promising combination of methods from Natural Language Processing and Artificial Intelligence. The approach naturally generalizes to related paraphrasing tasks such as shortening or simplifying a given text.
dblp:conf/coling/SteinHB14 fatcat:7mogda74crernf3ikscit4x2fu