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Improving the Quality of Online Search Services: On the Service Multi-selection Problem

机译:提高在线搜索服务的质量:关于服务多选问题

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The global objective of this study is to propose solutions for improving the quality of online search services. We consider the special case where the processing of requests submitted to such services consists of: the querying of several types of sub-services followed by the composition of the output produced the sub-services. This could be the case for instance of a booking service that proposes travel packs including: hotel reservation, car rental and flight booking. We propose to improve the quality of such services with the multi-selection problem. The goal in this problem is to select the subset of sub-services of each type to use in the the processing of search request. The selection must ensure that we maximize the quality of the results we could expect from the search. The multi-selection problem is close to the service selection problem. However, while in the latter, we are interested in a unique sub-service per type, in the former, we want to choose a subset of sub-services. Our paper introduces a theoretical formulation of the problem and demonstrates its NP-hardness. We also propose two approaches for the resolution. The first approach is based on Integer Linear Programming. The second approach combines parallel algorithm portfolio and sampling techniques. Finally, we make a comparative evaluation of the approaches based on practical scenarios.
机译:这项研究的全球目标是提出提高在线搜索服务质量的解决方案。我们考虑一种特殊情况,其中处理提交给此类服务的请求包括:查询几种类型的子服务,然后查询产生子服务的输出的组成。例如,预订服务可能会提供旅行套餐,包括:酒店预订,汽车租赁和航班预订。我们建议通过多选问题来提高此类服务的质量。此问题的目标是选择每种类型的子服务的子集以用于处理搜索请求。选择必须确保我们最大程度地提高搜索结果的质量。多选问题接近于服务选择问题。但是,在后者中,我们对每种类型的唯一子服务感兴趣,而在前者中,我们希望选择子服务的子集。本文介绍了该问题的理论公式,并证明了其NP硬度。我们还提出了两种解决方法。第一种方法基于整数线性规划。第二种方法结合了并行算法组合和采样技术。最后,我们根据实际情况对这些方法进行了比较评估。

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