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Framework of blog data based multi-criteria weighted points of interest graph for trip planning

机译:基于博客数据的多准则加权兴趣点图的旅行计划框架

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摘要

The task of planning an efficient itinerary has remained laborious and complicated with the bulk of online information imposing difficulty of selecting places and their visiting order. Therefore, a trip planning system generally aims to propose popular points of interests (POIs) and routes in a region structured as a POI graph. The proposed framework aims to utilize travel blogs to accumulate this information. Accordingly, existing approaches have employed frequent pattern mining to construct a POI graph that results in frequency-weighted POIs and route recommendation. The suggested model incorporates a multi-criteria weighting scheme that is contrary to the conventional POI graph. To facilitate travel decision-making, the proposed framework treats frequency measure as an initial weight and further processes blog entries to extract the opinions related to POIs and spatial information between POIs weighting nodes and edges, respectively. A final consolidated weight for each component is computed using defined functions. The contribution has significance for ordinary travelers in efficiently planning their itineraries, as well as for destination management organizations, in realizing the travelling trend and designing tourism products and strategies accordingly.
机译:计划有效行程的任务仍然很艰巨且复杂,因为大量的在线信息会给选择地点和访问顺序带来困难。因此,旅行计划系统通常旨在提出在构造为POI图的区域中的热门景点(POI)和路线。拟议的框架旨在利用旅行博客来积累此信息。因此,现有方法已采用频繁的模式挖掘来构造POI图,该POI图会导致频率加权POI和路线推荐。建议的模型采用了与传统POI图相反的多标准加权方案。为了方便旅行决策,提出的框架将频率量度视为初始权重,并进一步处理博客条目以提取与POI相关的意见以及POI加权节点和边缘之间的空间信息。使用定义的函数计算每个组件的最终合并权重。对于普通旅客有效地计划行程以及目的地管理组织,实现旅行趋势以及相应地设计旅游产品和策略,该贡献具有重要意义。

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