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- W4285173693 abstract "In the field of knowledge discovery for multi-source homogeneous data, for an entity, its correct value is found by resolving conflicts among multiple sources of information. However, due to missing values and inefficient entity matching, a single entity’s information is often insufficient in practical applications. This phenomenon requires pattern discovery to discover information shared by entities from a collective set of entities and then use the discovered patterns to identify the related truths. In this chapter, we introduce pattern discovery for truth discovery and formulate it as an optimization problem [1]. To solve such a problem, we propose an algorithm called $$textsf {PatternFinder}$$ that jointly and iteratively learns the variables. We give a motivate example in Sect. 4.1 and define the problem of pattern discovery in Sect. 4.2. Section 4.3 describes the overall solution and the main component PatternFinder. We conclude the chapter with final remarks in Sect. 4.4." @default.
- W4285173693 created "2022-07-14" @default.
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- W4285173693 date "2022-01-01" @default.
- W4285173693 modified "2023-10-16" @default.
- W4285173693 title "Pattern Discovery for Heterogeneous Data" @default.
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- W4285173693 doi "https://doi.org/10.1007/978-981-19-1879-7_4" @default.
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