Journal of Geo-information Science

Research and Implementation of Travel Itinerary Chain Extraction Method Based on the DeepSeek Model

CHEN Minjie, ZHANG Zheng, CAO Yibing, ZHANG Jiangshui, YANG Zhenkai, LU Zhenglun

Journal of Geo-information Science, 2026, 28(3): 722-735. DOI: 10.12082/dqxxkx.2026.250487

方法	Precision_macro			Recall_macro			F1_macro
方法	马蜂窝	去哪儿	携程网	马蜂窝	去哪儿	携程网	马蜂窝	去哪儿	携程网
本文方法	94.89	92.87	93.50	95.60	94.65	95.89	94.73	93.04	94.38
HanLP	89.54	87.46	88.25	96.27	94.83	96.34	90.16	88.47	89.54

Tab. 6 Comparison of travel node extraction results （%）

Other figure/table from this article

Fig. 1 Overall flow chart of travel itinerary chain extraction
Fig. 2 Travel itinerary chain description model
Fig. 3 Prompt strategy for generating travel itinerary chain data
Tab. 1 Detailed content and description of data format constraints
Fig. 4 Travel itinerary chaingeolocationprocess
Tab. 2 Problems in the extraction results of travel node names
Tab. 3 Examples of fields in an external knowledge file
Fig. 5 Temporal distribution of the extracted travel itinerary chains
Fig. 6 Spatial distribution of the extracted travel itinerary chainsin Henan Province
Fig. 7 Spatial distribution of travel nodes by different platforms in Henan Province
Fig. 8 Top 20 travel nodes by route frequency
Fig. 9 The number of 5A and 4A scenic spots in each city of Henan Province
Fig. 10 Scatter plot of the number of 5A and 4A-level scenic spots versus the frequency of travel nodes
Tab. 4 Macro average of precision, recall, and F1 score for extracted travel nodes （%）
Tab. 5 Similarity statistics of extracted travel itinerary chains with different lengths （%）
Tab. 7 Extracted travel itinerary chain similarity comparison （%）