Research On Users' Online Medical Information Search Intention Based On Text Minin

The explosive growth of the Internet medical information service market has brought the opportunity for Internet medical services.China’s medical service is a complex and unbalanced market,in which the giant public hospitals and large hospitals control most of the medical market.09 years of medical reform five-year plan proposed to deepen the reform of public hospitals,the first point is to improve the service system,which is also being actively implemented.It is advocated to optimize the layout of public hospitals and establish a division of labor between public hospitals and urban and rural primary health care institutions,some development of general departments and non-suspicious diseases will be decentralized to primary care,so that patients can seek medical treatment locally.To carry out optimization,large hospitals need to know what patients care about and what diseases are currently more prevalent.Primary care providers also need to have an in-depth understanding of patients and a reasonable allocation of relevant medical resources to cultivate patients’ trust and strive for maximum patient retention.All these can be referred to and learned from the user search analysis of user search text of Internet medical information search.In contrast to the research on online medical information,which is mainly focused on the understanding of medical professional data,integration of medical solutions and patient case studies,there is a significant lack of research on the user aspects of user medical information search research.In this thesis,we mainly focus on the search text data in the process of online medical information search,which has not been covered by the current research,and combine data analysis and mining methods such as intent classification,topic clustering and text mining,etc.We use Fasttetxt to classify different search texts according to intent tags,we use BTM model to mine the topics of different intent tags combined with TF-IDF,co-occurrence value,correlation coefficient,etc.to explore the characteristics of alternative search situations in online medical information search,the scope of searchers’ main concerns under different search intent tags,hot spots and the relationship mining of some high co-occurrence words.The background of possible reasons behind their generation is further analyzed,and the issues of search terminology habits and common phrases for different intent searches are summarized.This study can provide a reference for the reasonable allocation of online medical information resources.By analyzing the main flow of text for different intent tags and analyzing the hotspots and search habits under different intent tags,we can more accurately locate the demand for medical resources and adjust the corresponding resource allocation in a targeted manner,thus alleviating the tight situation of online medical information resources.By analyzing and studying search texts,we can gain insight into users’ language habits and focus of attention,thus providing effective analysis for online medical services.This will help to better serve users,capture the market,improve the service treatment level and increase user satisfaction.At the same time,it also provides effective guidance for service providers to better meet customers’ needs and improve service quality.It can have a positive impact on medical information service providers and personnel such as information search platforms,consultation platforms and information-based service providers.Based on the text mining analysis,this paper reveals that the main intention of internet users for searching medical information on the internet is to collect the diagnosis and treatment of diseases,the main focus of the whole search focuses on women’s topics,as well as children and childbearing,and reveals the differences between users’ attention to hot topics and search habits under different consent labels It is revealed that there is indeed substitution search behavior in network medical information search,among which children’s substitution search is the most,followed by the Elder’s substitution search and the partner’s substitution search,while the elder’s substitution search has more female substitution search,in the partner substitution search,there is the opposite sex of the substitute searcher before and after the relationship is established.These conclusions can enrich the content of medical information search,improve and optimize the strategy of medical information services and adjust the structure of network medical information resources.