最优路线覆盖搜索使用空间关键字覆盖

B. S. Ayyappa Kumar, A. S L C Sekhara Kumari
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引用次数: 1

摘要

利用空间数据库中的关键词来表示业务特征。在从空间数据库中检索数据时,出现了一个问题,称为最接近关键字覆盖搜索,这是由于查询关键字集和它们之间的对象间距离最小而出现的问题。最佳决策的对象评估取决于可用性和关键字评级的增加。最接近关键字搜索扩展到最佳关键字覆盖处理对象间距离和关键字评级在更标准的方式。最初采用基线算法来克服上述问题,但它并不适用于实时数据库,为了克服这一问题,提出了一种新的算法,并将其命名为关键字最近邻扩展算法,它比基线算法减少了候选关键字覆盖的数量。与基线算法相比,K-NNE算法得到了局部最优解,产生的新候选关键字覆盖较少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Best optimal route cover search using spatial keyword covering
Business features are indicated with the help of keywords in spatial database. While retrieving data from spatial database a problem occurs and named as Closest Keyword Cover Search, problem occurs due to set of query keywords and minimum inter object distance between them. Object evaluation for the best decision making depends on the increase of availability and keyword rating. Closest keywords search is extended to Best Keyword Cover deals with inter object distance and keyword rating in more standard manner. Initially baseline algorithm is used to overcome the problem mentioned and it is not applicable for real time databases, in order to overcome this a new algorithm is proposed and named as Keyword Nearest Neighbor Expansion it reduces the number of candidate keyword covers compared to baseline algorithm. With the help of K-NNE algorithm local best solution is obtained and generates less new candidate keyword covers compared to baseline algorithm.
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