Research And Application Of Information Retrieval Algorithm In Intelligent Tourism

With the gradual improvement of living standards,tourism has become one of the vast majority of people's leisure activities,and in today's rapid trend of information technology,when users make travel plans,they tend to give priority through the search platform to query the relevant tourism information.However,the amount of tourism information stored in the Internet is increasingly large and increasingly complex,and users pay more attention to the relevance of the information provided by the search platform.After the user enters the search item through the retrieval platform,always wants to find the most relevant and reliable travel information with the search items at the top of the search results.How to present the most relevant and reliable source of information as the search results to users,and let users really enjoy the wisdom of tourism is the search platform to solve one of the urgent problems.Therefore,search ranking algorithm has become one of the most important research directions.In this paper,the following research is carried out on the information retrieval algorithm of intelligent tourism:(1)This paper analyzes the principle of the traditional Page Rank algorithm,and studies the deficiency of the traditional Page Rank algorithm and the improvement of the PageRank algorithm.On the basis of previous studies,a SM-PageRank algorithm that based on the similarity of the page of link is proposed.In this algorithm,the similarity between the page and its linked web pages is introduced into the calculation of PageRank algorithm,we can reasonably assign the weight of the link page by this calculation.(2)The user interest model is used to sort the results again.The principle is: to establish user interest model for each user,when users search,the search engine returns the result set of the first ranking,then calculates the similarity by the user interest model and each page in result set,and recalculates the score value of each page by the similarity,finally the results are sorted descendly according to the new scores and the final results are displayed to the user.Because of the second ranking is based on the establishment of user interest model.Therefore,in order to better sort the first search result set by the user interest model,it is necessary to analyze the user's interest,the establishment of user interest model and the renewal of user interest model.(3)Using Nutch and Solr to build the search experimental platform of intelligent tourism.Firstly,Nutch is used to fetch the experimental datasource,then the SM-Page Rank algorithm and the traditional PageRank algorithm are applied to Nutch respectively.IKAnalyzer which is a chinese word segmentation tool is used in Solr,and finally call the application services provided by Solr for search service.The experimental results show that,compared with the traditional Page Rank algorithm,the search results of the SM-PageRank algorithm are more accurate,and the accuracy of the search results is further improved by the application of the second ranking method,which is more suitable for users.