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Procedure and system of construction of actual, current travel rates

机译:实际,当前旅行费率的构建程序和系统

摘要

A system for providing a plurality of destination options comprising: - a fee learning component (110, 210) connectable to at least one computerized reservation system; - a pair of structures (220, 230) of updatable data from the fare learning component (110), and storing a plurality of travel data, the aforementioned travel data comprising at least one origin (221), a destination (225), a reserve price and some reserve dates; comprising the pair of data structures, on the one hand, a graph of nodes with nodes and edges in which the nodes are the travel destinations and in which each of the edges refers to a lower travel rate among the two nodes that connect, and on the other hand, a rate tree built for each edge of the graph and that includes a root that maintains the lowest trip rate on the edge; - a buyer engine (105) to accept at least one origin (610) and an interval (630, 640) of dates and interrogate the data structure (220, 230) to generate the plurality of destination options corresponding to the origin (610) and to the dates reserved within the interval (630, 640) of dates; - a rate route extraction engine (200), configured to extract rate routes from the pair of data structures in order to determine the least expensive rate routes, said rate route extraction engine configured to construct , for each origin and destination pair, a stack maintained organized as a binary tree and configured to accumulate a predetermined maximum number (k) of less expensive fare routes between the origin and the destination during extraction.
机译:一种用于提供多个目的地选项的系统,包括:-可连接至至少一个计算机预订系统的费用学习组件(110、210);以及-来自票价学习组件(110)的可更新数据的一对结构(220、230),并存储多个旅行数据,上述旅行数据包括至少一个起点(221),目的地(225),底价和一些底价;一方面,它包含一对数据结构,另一方面是具有节点和边的节点的图,其中节点是旅行的目的地,每个边指的是连接的两个节点中较低的旅行率;另一方面,为图表的每个边缘构建的速率树,其中包括在边缘保持最低跳闸速率的根; -买方引擎(105)接受至少一个起点(610)和日期间隔(630、640)并询问数据结构(220、230)以生成与起点相对应的多个目的地选项(610)以及在日期间隔(630,640)内保留的日期; -速率路由提取引擎(200),其被配置为从该对数据结构中提取速率路由以确定最便宜的速率路由,所述速率路由提取引擎被配置为针对每个始发和目的地对构造维护的堆栈。将其组织为二叉树,并配置为在提取过程中在出发地和目的地之间累积预定最大数量(k)的较便宜的票价路线。

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