Research On The Method Of Constructing Event Evolutionary Graph Of Housing Price Changes

Since the real estate industry was recognized as a pillar industry of the national economy in 2003,the real estate industry has entered a period of rapid development and prosperity,but with it comes increasingly serious livelihood issues,such as excessive housing prices and housing supply.The structure is unreasonable.Excessive housing prices not only make the housing needs of urban and rural residents unsatisfactory,but may also cause serious economic harm and even cause a global economic crisis.Therefore,a timely,accurate and comprehensive understanding of the relevant influencing factors that promote changes in housing prices will help relevant government departments to make targeted policy formulations,which is of great significance to fundamentally controlling housing price stability and maintaining social and financial order.In this research,the change of housing price is regarded as a complex event,and the construction scheme of event map suitable for the field of housing price change is designed to analyze the evolution law of housing price change.Firstly,we use web crawler to capture the real estate news of Baidu news and Sina News as the research data,and then clean the original data and process the natural language.Then,combined with the relevant characteristics of the news text of house price changes and the basis for the classification of causal types proposed in this study,a causal event extraction method suitable for the news text in the field of house price change is designed.Then,How Net is used to calculate the semantic similarity between events to generalize the events,so as to construct the causal chain.Considering the influence of time factor on the transition probability between events,the time decay term is introduced to optimize the calculation method of transition probability.Through the analysis of housing price change map,find the evolution law of the key influencing factors of housing price change,so as to guide the normal operation of the real estate market.