Reluctant Paraphrase: Textual Restructuring under an Optimisation Model

TL;DR

This paper introduces a computational model for paraphrasing that minimizes text modifications while satisfying external constraints like length and readability, using optimization techniques within a formal framework.

Contribution

It presents a novel optimization-based framework for reluctant paraphrasing, integrating constraint handling and minimal change principles into a computational system.

Findings

Developed a formal model for reluctant paraphrasing

Outlined the use of mathematical optimization techniques

Integrated the framework into the XTAG paraphrase system

Abstract

This paper develops a computational model of paraphrase under which text modification is carried out reluctantly; that is, there are external constraints, such as length or readability, on an otherwise ideal text, and modifications to the text are necessary to ensure conformance to these constraints. This problem is analogous to a mathematical optimisation problem: the textual constraints can be described as a set of constraint equations, and the requirement for minimal change to the text can be expressed as a function to be minimised; so techniques from this domain can be used to solve the problem. The work is done as part of a computational paraphrase system using the XTAG system as a base. The paper will present a theoretical computational framework for working within the Reluctant Paraphrase paradigm: three types of textual constraints are specified, effects of paraphrase on text are described, and a model incorporating mathematical optimisation techniques is outlined.