Trackers have become popular devices these days. They are extensively used to record sports activities (e.g., hiking, skiing), mainly in terms of GPS trajectories, which can be shared on social networking platforms with other users looking for leisure tips. Notably, as the number of available trajectories drastically increased over time, in many cases, it has become challenging, if not impossible, the extensive evaluation of all possible alternatives and the manual selection of the most suitable one. Paths are characterized by multiple features (e.g., dirt, asphalt), and a good representation is needed to satisfy user needs. Moreover, paths can be composed to generate new routes. This calls for a recommender system capable to handle both the multi-feature path representation and the implicit definition of alternatives by composition. This paper suggests a novel approach that features a richer trajectory representation based on a semantic annotation to describe significant path features. Annotations are then used for automatic recommendation of new paths that maximize the presence of characteristics matching the user preferences. Finally, a class of algorithm variants is evaluated using an off-line validation process and compared with a baseline solution to test the underlying assumptions.

中文翻译：

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关于多功能路径的组成和建议：综合方法

跟踪器已经成为当今流行的设备。它们被广泛地用于记录体育活动（例如，远足，滑雪），主要是在GPS轨迹方面，可以在社交网络平台上与寻找休闲技巧的其他用户共享。值得注意的是，随着时间的推移，可用轨迹的数量急剧增加，在许多情况下，即使不是不可能，对所有可能的替代方案进行广泛评估并手动选择最合适的替代方案也变得充满挑战。路径具有多个特征（例如，灰尘，沥青），并且需要良好的表示方式来满足用户需求。此外，可以组成路径以生成新路线。这就需要一种推荐器系统，该系统能够同时处理多功能路径表示和按组成部分隐式定义替代项。本文提出了一种新颖的方法，该方法以基于语义注释的丰富轨迹表示来描述重要的路径特征。然后，将批注用于自动推荐新路径，以使与用户首选项相匹配的特征的存在最大化。最后，使用离线验证过程评估一类算法变体，并将其与基准解决方案进行比较以测试基本假设。