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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (11): 79-88    DOI: 10.11925/infotech.2096-3467.2019.0498
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Route Recommendation Based on Two-way Link Analysis of Urban Name Entities
Guanghui Ye1(),Jinqing Yang2
1 School of Information Management, Central China Normal University, Wuhan 430079, China
2 School of Information Management, Wuhan University, Wuhan 430072, China
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Abstract  

[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.

Key wordsGeographic Name Entity      Two-way Link      Fuzzy Retrieval      Route Recommendation      Data Profiling     
Received: 12 May 2019      Published: 18 December 2019
ZTFLH:  G350  
Corresponding Authors: Guanghui Ye     E-mail: 4081@163.com

Cite this article:

Guanghui Ye,Jinqing Yang. Route Recommendation Based on Two-way Link Analysis of Urban Name Entities. Data Analysis and Knowledge Discovery, 2019, 3(11): 79-88.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2019.0498     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2019/V3/I11/79

地名实体名 地名实体编号 轨迹链编号
深水埗 1 1
昂坪 2 1
长洲岛 1 801
地名实体名 轨迹链编号 链入隶属度 链出隶属度
昂坪 1 0.047 0.098
昂坪 1 0.064 0.138
佐敦道 801 0.013 0.073
极小项 地名实体对应轨迹链集合 极小项对应模糊集
$\phi $(1,0,0) 沙田 A=$\phi $ $\phi $
旺角 U-B
湾仔 U-C
(1,0,1) 沙田 A=$\phi $ $\phi $
旺角 U-B
湾仔 C={2,3,8,19,26,34,39,72,121,136,199,272,406,504,575,635}
(1,1,0) 沙田 A=$\phi $ $\phi $
旺角 B={8,26,34,39,73,88,136,199,205,216,272,349,375,406,635,640,789}
湾仔 U-C
(1,1,1) 沙田 A=$\phi $ $\phi $
旺角 B={8,26,34,39,73,88,136,199,205,216,272,349,375,406,635,640,789}
湾仔 C={2,3,8,19,26,34,39,72,121,136,199,272,406,504,575,635}
(0,1,1) 沙田 U {8,26,34,39,136,199,272,406,635}.
旺角 B={8,26,34,39,73,88,136,199,205,216,272,349,375,406,635,640,789}
湾仔 C={2,3,8,19,26,34,39,72,121,136,199,272,406,504,575,635}
轨迹链编号 隶属度 轨迹链编号 隶属度
8 0.332 199 0.300
26 0.301 272 0.282
34 0.314 406 0.277
39 0.258 635 0.278
136 0.311
极小项 地名实体对应轨迹链集合 极小项对应模糊集
(1,0,0) 沙田 A=$\phi $ $\phi $
旺角 U-B
湾仔 U-C
(1,0,1) 沙田 A=$\phi $ $\phi $
旺角 U-B
湾仔 C={8,26,88,199}
(1,1,0) 沙田 A=$\phi $ $\phi $
旺角 B={3,8,26,34,39,73,88,136,199,205,245,272,375,406,475,495,620,635,638,717}
湾仔 U-C
(1,1,1) 沙田 A=$\phi $ $\phi $
旺角 B={3,8,26,34,39,73,88,136,199,205,245,272,375,406,475,495,620,635,638,717}
湾仔 C={8,26,88,199}
(0,1,1) 沙田 U {8,26,88,199}.
旺角 B={3,8,26,34,39,73,88,136,199,205,245,272,375,406,475,495,620,635,638,717}
湾仔 C={8,26,88,199}
轨迹链编号 隶属度 轨迹链编号 隶属度
8 0.283 88 0.259
26 0.266 199 0.263
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