Abstract
In order to solve the problem of large-scale user attribute identification of real estate advertising push, a social network real estate advertising push method based on big data analysis is proposed. First, according to the real estate advertising push strategy of social networks, it is refined and implemented level by level, focusing on specific target customer groups. Given the initial link of the original blog of the advertiser, the text features of the real estate advertising project are extracted by extracting the basic information of all the blogs in a circular manner. Secondly, analyze the social relations of users, mine the characteristics of social network users based on big data analysis, realize the classification and recognition of user attributes, and calculate the similarity between the two using similarity calculation formula. Finally, the calculation results are sorted in reverse order of similarity to generate a real estate advertisement recommendation list for users. The design method is tested on the epinions data set, and the test results show that the design method can improve the accuracy of recommendation and reduce the overall running time.
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Du, Y., Li, X. (2023). Social Network Real Estate Advertisement Push Method Based on Big Data Analysis. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-28787-9_46
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DOI: https://doi.org/10.1007/978-3-031-28787-9_46
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