Data integration based approach to find shortest path within a city for different time periods

Sudipta Kanjilal, S. Sen
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Abstract

Traditional data mining usually deals with data from single domain, however in modern day business applications the data may come from different domain for single application. Data sets are of multiple modalities. Each of them may have a different representation, distribution, scale and density. Data Integration techniques aggregate several domains of data sets and then represent in a unified form so that they can be used for data mining. In this research work data integration is considered in terms of the data collected from multiple modes of communication within a city and these data have been integrated and organized to infer more information. Here more information refers to generation of more numbers of routes in a city by combining multiple modes of communication. Further, this research work proposes an optimization in terms of searching path which is shortest in terms of time. The proposed methodology is executed on the historical data of different instances of day as well as different day of the week so that the relevant conditions or constraints associated with the traffic are included.
基于数据集成的方法寻找城市内不同时间段的最短路径
传统的数据挖掘通常处理来自单一领域的数据,而在现代业务应用中,单个应用程序的数据可能来自不同的领域。数据集具有多种模态。它们中的每一个都可能有不同的表现形式、分布、规模和密度。数据集成技术将多个领域的数据集聚合在一起,然后以统一的形式表示,以便用于数据挖掘。在本研究工作中,数据整合是指从一个城市内的多种通信方式收集的数据,并将这些数据进行整合和组织,以推断出更多的信息。这里更多的信息是指通过多种通信方式的结合,在一个城市中产生更多的路线。进一步,本研究工作提出了一种搜索路径在时间上最短的优化方法。建议的方法是根据一天中不同实例以及一周中不同日子的历史数据执行的,以便包括与交通有关的相关条件或限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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