基于城市地名实体双向链接分析的路线推荐研究

Route Recommendation Based on Two-way Link Analysis of Urban Name Entities

【目的】已有线路推荐研究较少考虑地名实体之间的次序,为此设计了基于城市地名实体双向链接分析的路线推荐方法。【方法】以特定场景下不同地名实体形成的有向加权网络为基础数据源,循环计算不同轨迹链隶属于各个地名实体对应理想集的链入和链出值,进而在通过布尔逻辑和位置限定运算符表达用户查询需求的基础之上,融合模糊检索算法,实现用户查询与轨迹链的精确匹配。【结果】本文所提算法推荐准确率为0.75,高于TF-IDF推荐算法和不考虑地名实体次序的推荐算法,但召回率无优势;随着加权网络规模的增大,推荐准确率与召回率呈现出明显的反向关系。【局限】未考虑对象属性数据对推荐结果的影响。【结论】本文方法融合了基于统计分析与语义分析的推荐算法,可快速生成备选路线及推荐指数。

[Objective]This study proposes a route recommendation method based on two-way link analysis of geographic name entities,aiming to improve the results with entity properties.[Methods]Firstly,we collected data from the directed weighted network of different place-name entities in specific scenarios.Then,we calculated the chain-in and chain-out values of different trajectory chains belonging to the ideal set of place-name entities.Finally,based on the Boolean logic and position-qualifying elements for user’s queries,we applied the fuzzy search algorithm to match user queries and track chains.[Results]The precision of proposed algorithm was 0.75,which is higher than traditional recommendation methods.However,the recall rate did not change significantly.As the increasing of the weighted network scale,the precision and recall rates showed a clear inverse relationship.[Limitations]We did not examine the impacts of the object attribute data on the recommendation results.[Conclusions]The proposed method combines the recommendation algorithms based on statistical and semantic analysis,which can quickly generate alternative routes and recommendation index.