We model the problem of monolingual textual alignment as a Quadratic Assignment Problem (QAP) which simultaneously maximizes the global lexicosemantic and syntactic similarities of two sentence-level texts. Because QAP is an NP-complete problem, we propose a branch-and-bound approach to efficiently find an optimal solution. When compared with other methods and studies, our results are competitive.

The quadratic assignment problem (QAP) was first proposed by Koopmans and Beckman [5] in the context of the plant location problem. Given n facilities, represented by the set F f1 fn , and n locations represented by the set L l1 ln , one must determine to which location each facility must be assigned. Let An n ai j be a matrix where ai j represents the flow between facilities fi and f j. Let Bn...

We introduce the problem of Task Assignment and Sequencing (TAS), which adds the timeline perspective to expert crowdsourcing optimization. Expert crowdsourcing involves macrotasks, like document writing, product design, or web development, which take more time than typical binary microtasks, require expert skills, assume varying degrees of knowledge over a topic, and require crowd workers to b...