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- W3202231826 abstract "Data consistency detection is a research hotspot in the field of data mining. Traditional data mining algorithms assume that the data is static. The current data classification models can handle static data well, but most of the data has the characteristics of huge scale and diverse changes. The performance of the classification model will be greatly reduced with changing data, so how to effectively detect the changes of the data is a wideconcern in the academic fields. By using decision tree as the background, and If-then rule as the core content of the data set, this paper discusses the feasibility of using rule interactive matching to detect the consistency. Further, a data consistency detection method based on interactive matching (IM-CC detection method) is given, and then several common UCI data sets are combined to analyze the characteristics and performance of the algorithm. Experimental results show that IM-CC has good interpretability and operability, can concisely integrate decision-making awareness into the decision-making process. So it has a wide range of application prospects." @default.
- W3202231826 created "2021-10-11" @default.
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- W3202231826 date "2021-07-23" @default.
- W3202231826 modified "2023-10-18" @default.
- W3202231826 title "Research on Data Consistency Detection Method Based on Interactive Matching" @default.
- W3202231826 cites W2009727399 @default.
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- W3202231826 doi "https://doi.org/10.1145/3478905.3478979" @default.
- W3202231826 hasPublicationYear "2021" @default.
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