Advanced fast nearest neighbor search with keywords over spatial database

Madhvi Sharma, Shaila Chugh
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引用次数: 2

Abstract

A search engine is able to efficiently support novel forms of spatial queries which are integrated with keyword explore. The accessible solutions to such queries also acquire prohibitive space consumption or are unable to give real time answers. As today's need is smart search from search engine not just what they query but relevant to query and similar to that query and where they actually find that product, place or person in real world. To provide such smart search results fast nearest neighbor search with keywords technique by using spatial inverted index (SI-index) has been proposed by researchers. This technique has great efficiency to provide results but processes huge data to fulfill queries. To overcome huge data pre-processing, proposed algorithm reduces no of objects processed by this technique to minimize the memory and processing cost. Proposed technique uses limits to fetch limited objects from the dataset or database. Experiments show great improvement of AFNNSK over FNNSK.
先进的快速最近邻搜索与关键字在空间数据库
搜索引擎能够有效地支持与关键字搜索相结合的新形式的空间查询。此类查询的可访问解决方案也会占用过多的空间,或者无法给出实时答案。因为今天的需求是搜索引擎的智能搜索,不仅仅是他们查询的内容,还有与查询相关和相似的查询,以及他们在现实世界中实际找到的产品,地点或人物。为了提供这样的智能搜索结果,研究人员提出了基于空间倒排索引(SI-index)的关键词快速近邻搜索技术。这种技术在提供结果方面效率很高,但要处理大量数据来完成查询。为了克服海量数据的预处理问题,该算法减少了所处理对象的数量,最大限度地降低了内存和处理成本。建议的技术使用限制从数据集或数据库中获取有限的对象。实验表明,AFNNSK比FNNSK有很大的改进。
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