In advertising, slogans are used to enhance the recall of the advertised product by consumers and to distinguish it from others in the market. Creating effective slogans is a resource-consuming task for humans. In this paper, we describe a novel method for automatically generating slogans, given a target concept (e.g., car) and an adjectival property to express (e.g., elegant) as input. Additionally, a key component in our approach is a novel method for generating nominal metaphors, using a metaphor interpretation model, to allow generating metaphorical slogans. The method for generating slogans extracts skeletons from existing slogans. It then fills a skeleton in with suitable words by utilizing multiple linguistic resources (such as a repository of grammatical relations, and semantic and language models) and genetic algorithms to optimize multiple objectives such as semantic relatedness, language correctness, and usage of rhetorical devices. We evaluate the metaphor and slogan generation methods by running crowdsourced surveys. On a five-point Likert scale, we ask online judges to evaluate whether the generated metaphors, along with three other metaphors generated using different methods, highlight the intended property. The slogan generation method is evaluated by asking crowdsourced judges to rate generated slogans from five perspectives: (1) how well is the slogan related to the topic, (2) how correct is the language of the slogan, (3) how metaphoric is the slogan, (4) how catchy, attractive, and memorable is it, and (5) how good is the slogan overall. Similarly, we evaluate existing expert-made slogans. Based on the evaluations, we analyze the method and provide insights regarding existing slogans. The empirical results indicate that our metaphor generation method is capable of producing apt metaphors. Regarding the slogan generator, the results suggest that the method has successfully produced at least one effective slogan for every evaluated input.

中文翻译：

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口号的计算生成

在广告中，标语用于增强消费者对所宣传产品的回忆，并将其与市场上的其他产品区分开来。创建有效的口号对人类来说是一项耗费资源的任务。在本文中，我们描述了一种自动生成标语的新方法，给定目标概念（例如，汽车）和要表达的形容词属性（例如，优雅）作为输入。此外，我们方法中的一个关键组成部分是使用隐喻解释模型生成名义隐喻的新方法，以允许生成隐喻口号。生成标语的方法是从现有标语中提取骨架。然后，它利用多种语言资源（例如语法关系库、以及语义和语言模型）和遗传算法来优化多个目标，例如语义相关性、语言正确性和修辞手段的使用。我们通过进行众包调查来评估隐喻和口号生成方法。在李克特五点量表上，我们要求在线评委评估生成的隐喻以及使用不同方法生成的其他三个隐喻是否突出了预期的属性。口号生成方法是通过要求众包评委从五个角度对生成的口号进行评估：（1）口号与主题的相关程度如何，（2）口号的语言是否正确，（3）口号的隐喻性如何口号，（4）它是多么吸引人，有吸引力和令人难忘，以及（5）口号总体上有多好。同样，我们评估现有的专家口号。基于评估，我们分析了该方法并提供了有关现有口号的见解。实证结果表明，我们的隐喻生成方法能够产生恰当的隐喻。关于口号生成器，结果表明该方法成功地为每个评估的输入生成了至少一个有效的口号。