With the rapid increase in the number of Apps, the requirement of users has also become extremely complex. Developers have to continuously acquire innovative requirements that provide the guideline for developing more competitive products. However, traditional methods to acquire requirements are not suitable for the App development due to the disadvantage that it cannot interact with users directly. Besides, some methods that use text and data analysis to acquire requirements automatically are hard to expand innovative products because they are often confined to the specific App or the same domain. Therefore, to attract more new users, developers try to find new portable inspiration from other domains for enriching the functions of the App. In this article, we propose a feature extraction method from the descriptions of Apps and use similarity matching to acquire cross-domain requirements. Our experiments have verified that the Precision, the Recall, and the F-measure are all as high as 80% of our feature extraction method. Besides, the requirements list we recommend also makes a good performance in terms of reusability with the average Reuse Rank of 59.33% and average Adjusted Functional Points of 7.49, the adaptability gets an average score of 3.3, and the average score of operability is 3.

中文翻译：

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一种基于语法直接技术的跨域需求获取方法

随着App数量的快速增长，用户的需求也变得异常复杂。开发人员必须不断获得创新需求，为开发更具竞争力的产品提供指导。但是，传统的需求获取方式不能直接与用户交互，不适合App开发。此外，一些通过文本和数据分析自动获取需求的方法，由于往往局限于特定的App或同一个领域，因此很难扩展创新产品。因此，为了吸引更多的新用户，开发者尝试从其他领域寻找新的便携灵感，丰富App的功能。在本文中，我们提出了一种从应用程序描述中提取特征的方法，并使用相似性匹配来获取跨域需求。我们的实验已经证实，Precision、Recall 和 F-measure 都高达我们特征提取方法的 80%。此外，我们推荐的需求列表在可重用性方面也有不错的表现，平均重用等级为59.33%，平均调整功能点为7.49，适应性平均得分为3.3，可操作性平均得分为3。