As a major type of continuous spatial queries, the moving spatial keyword queries have been studied extensively. Most existing studies focus on retrieving single objects, each of which is close to the query object and relevant to the query keywords. Nevertheless, a single object may not satisfy all the needs of a user, e.g., a user who is driving may want to withdraw money, wash her car, and buy some medicine, which could only be satisfied by multiple objects. We thereby formulate a new type of queries named the moving collective spatial keyword query (MCSKQ). This type of queries continuously reports a set of objects that collectively cover the query keywords as the query moves. Meanwhile, the returned objects must also be close to the query object and close to each other. Computing the exact result set is an NP-hard problem. To reduce the query processing costs, we propose algorithms, based on safe region techniques, to maintain the exact result set while the query object is moving. We further propose two approximate algorithms to obtain even higher query efficiency with precision bounds. All the proposed algorithms are also applicable to MCSKQ with weighted objects and MCSKQ in the domain of road networks. We verify the effectiveness and efficiency of the proposed algorithms both theoretically and empirically, and the results confirm the superiority of the proposed algorithms over the baseline algorithms.

中文翻译：

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有效处理移动集体空间关键字查询

作为连续空间查询的一种主要类型，移动空间关键词查询已经得到了广泛的研究。现有的大多数研究都集中在检索单个对象上，每个对象都靠近查询对象并与查询关键字相关。然而，单个对象可能无法满足用户的所有需求，例如，正在开车的用户可能想取钱，洗车和购买一些药品，而这只能由多个对象来满足。因此，我们制定了一种新型查询，称为移动集体空间关键字查询（MCSKQ）。此类查询连续报告一组对象，这些对象在查询移动时共同覆盖了查询关键字。同时，返回的对象还必须靠近查询对象并且彼此靠近。计算精确的结果集是一个NP难题。为了降低查询处理成本，我们提出了基于安全区域技术的算法，以在移动查询对象时保持准确的结果集。我们进一步提出了两种近似算法，以在精确范围内获得更高的查询效率。所有提出的算法也适用于带加权对象的MCSKQ和道路网络领域的MCSKQ。我们在理论上和经验上都验证了所提算法的有效性和效率，结果证实了所提算法优于基线算法的优越性。所有提出的算法也适用于带加权对象的MCSKQ和道路网络领域的MCSKQ。我们在理论上和经验上都验证了所提算法的有效性和效率，结果证实了所提算法优于基线算法的优越性。所有提出的算法也适用于带加权对象的MCSKQ和道路网络领域的MCSKQ。我们在理论上和经验上都验证了所提算法的有效性和效率，结果证实了所提算法优于基线算法的优越性。