Research On Residential District Livability Evaluation Based On Association Rules

"Livable" has become an important criterion for the competitiveness and attractiveness of cities and regions.The provinces and cities in the country have released the evaluation system of the livable level of the residential area.At present,most of the research on the livability index of residential area is based on the definition of the index and the establishment of the corresponding index system.In the presence of various indicators and index systems,the vast majority of indicators stay in the theoretical description,index data is only applicable for research institutions or government departments to be obtained,analyzed,it is not only difficult but also limited for the consumers to obtain the index data directly,and it is also difficult for consumers to make the comprehensive analysis towards the index data and use relevant information to guide the real estate consumer behavior.Firstly,this article carries on the analysis to the various existing index system,combined with the major real estate website and the actual survey data,select the relevant indicators is relatively intuitive,easy to be accepted by the terminal consumers,establish the index system of livable residential for ordinary consumers.Through the classification of the indicators of the data processing of the data points,the calculation of the residential area livable four stars base on this index system,and the higher the higher the degree of habitable area.The livable index database of residential district is built on the basis of the quantitative data of livable stars and index classification.Finally,the classicalApriori and Apriori based on partition are used to do data mining and analysis of association rules in the database.The experimental results show that the Apriori algorithm based on partition,it is better to to do the association rules mining of the residential areas with different livability for the acquisition of the key factors that affect the different livable level of the different residential district.It is found that the potential correlation between the livable indexes of the residential areas,and then provide comprehensive data guidance and decision support for the real estate consumer groups.