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Research on Travel Personalized Recommendation based on Web Crawler

摘要


In view of the lack of 'special price' oriented function software in the current market, it is recommended to recommend air tickets, hotels and appropriate tourist cities, use Python language to compile web crawlers, crawl the air tickets, hotels and scenic spots of Ctrip and qunar, and use spring boot By analyzing the data and information obtained, the special price recommendation and popular scenic spot recommendation in the current season are realized, which fills in the vacancy of "economical and applicable" on large-scale tourism websites, and provides viewing direction for users who want to plan their own travel routes.

參考文獻


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Cheng C C , Chen P L , Chiu F R , et al. Application of neural networks and Kano's method to content recommendation in web personalization[J]. Expert Systems with Applications An International Journal, 2009, 36(3p1):5310-5316.
Pinkerton B , Lazowska E , Zahorjan J . Abstract WebCrawler: Finding What People Want[D]. Dissertation Abstracts International, Volume: 61-11, Section: B, page: 5967.;Chairpersons: Edward La, 2000.

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