In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

[EX Q]: Words can be represented by composing the representations of subword units such as word segments, characters, and/or character n-grams. While such representations are effective and may capture the morphological regularities of words, they have not been systematically compared, and it is not understood how they interact with different morphological typologies. On a language modeling task, we present experiments that systematically vary (1) the basic unit of representation, (2) the composition of these representations, and (3) the morphological typology of the language modeled. Our results largely confirm previous findings that character representations are effective across many languages, though we find that a previously unstudied combination of character trigram representations composed with bi-LSTMs outperforms most other settings. However, we also find room for improvement: character models do not match the predictive accuracy of a model with access to explicit morphological analyses.
[EX A]: From Characters to Words to in Between: Do We Capture Morphology?

[EX Q]: In this article using Cuckoo Optimization Algorithm and simple additive weighting method the hybrid COAW algorithm is presented to solve multi-objective problems. Cuckoo algorithm is an efficient and structured method for solving nonlinear continuous problems. The created Pareto frontiers of the COAW proposed algorithm are exact and have good dispersion. This method has a high speed in finding the Pareto frontiers and identifies the beginning and end points of Pareto frontiers properly. In order to validation the proposed algorithm, several experimental problems were analyzed. The results of which indicate the proper effectiveness of COAW algorithm for solving multi-objective problems.
[EX A]: THE NEW HYBRID COAW METHOD FOR SOLVING MULTI-OBJECTIVE PROBLEMS

[EX Q]: This paper presents an adaptation of the harmony search algorithm to solve the storage allocation problem for inbound and outbound containers. This problem is studied considering multiple container type (regular, open side, open top, tank, empty and refrigerated) which lets the situation more complicated, as various storage constraints appeared. The objective is to find an optimal container arrangement which respects their departure dates, and minimize the re-handle operations of containers. The performance of the proposed approach is verified comparing to the results generated by genetic algorithm and LIFO algorithm. General Terms Container storage problem, metaheuristics.
[EX A]:
Harmony search to solve the container storage problem with different container types