论文标题
如何在WISP应用程序中使用JJCluster从不同类别中群群唯一的节点？
How to cluster nearest unique nodes from different classes using JJCluster in Wisp application?
论文作者
论文摘要
根据用户喜好找到最佳位置的工作是一项繁琐的任务。它需要手动研究和大量直观过程，以根据有关该地点的一些早期知识找到最佳位置。它主要是关于访问公开可用的空间数据，应用简单的算法根据给定的偏好汇总数据，并在地图上可视化结果。我们介绍了JJCluster，以消除对一个地方研究并实时可视化位置的严格方式。该算法在WISP应用程序中成功找到了城市的心脏。设计WISP应用程序的主要目的用于找到最接近一组偏好的未知地方的理想位置。我们还讨论了当今动态编程的先驱的各种优化算法，以及在数据混乱时需要可视化以查找模式的需求。但是，这种一般的聚类算法可以在其他领域使用，我们可以探索所有可能的偏好以最大程度地提高其效用。
The work of finding the best place according to user preference is a tedious task. It needs manual research and lot of intuitive process to find the best location according to some earlier knowledge about the place. It is mainly about accessing publicly available spatial data, applying a simple algorithm to summarize the data according to given preferences, and visualizing the result on a map. We introduced JJCluster to eliminate the rigorous way of researching about a place and visualizing the location in real time. This algorithm successfully finds the heart of a city when used in Wisp application. The main purpose of designing Wisp application is used for finding the perfect location for a trip to unknown place which is nearest to a set of preferences. We also discussed the various optimization algorithms that are pioneer of today's dynamic programming and the need for visualization to find patterns when the data is cluttered. Yet, this general clustering algorithm can be used in other areas where we can explore every possible preference to maximize its utility.
