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- W3166908727 abstract "Nowadays, mining user profiles from web log, and then recommending interested items becomes a research hot. In the meantime, user's behavior habits can be learned to improve the usage experience. However, current web frameworks are separated with the front-end and the back-end parts, and then the web logs are jumbled together. Always a single user's action can generate multiple logs, which makes it particularly difficult to recover user's behavior and analyse his habits. To overcome above difficulties, a sequence pattern mining method based on PrefixSpan is designed to extract the common sequence pattern of user's log as their operation behaviors. Further more, W-Kmeans is used to cluster their operation behaviors and summarize their habits. Finally, we design a multi-dimensional user profile label system to depict the user's features from multiple perspectives, and use the WordCloud to draw the profiles." @default.
- W3166908727 created "2021-06-22" @default.
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- W3166908727 date "2021-04-24" @default.
- W3166908727 modified "2023-09-26" @default.
- W3166908727 title "Towards Visualized User Profile Analysis from Massive Web Log" @default.
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- W3166908727 doi "https://doi.org/10.1109/icccbda51879.2021.9442590" @default.
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