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This is done through the Zingg pipe abstraction. Key Zingg Concepts Zingg learns 2 models on the data: Blocking Model One fundamental problem with scaling data mastering is that the number of comparisons increase quadratically as the number of input record increases. Zingg learns a clustering/...
has.entitySchemaAbstractionLevel A level of abstraction assigned to an Entity schema. Logical schema descriptions use complex dataTypes, inheritance, and entities as attributes. Resolved descriptions contain none of those things, only final trait and attribute sets are shown. A composition schema manipula...
it should result in enough information to start working on a conceptual data model, which is an abstraction of the logical model. Talking to the business, first of all, provides a complete picture of the business processes, which, in turn, provides information about the various...
Towards Sub-Word Level Compositions for Sentiment Analysis of Hindi-English Code Mixed Text Sentiment analysis (SA) using code-mixed data from social media has several applications in opinion mining ranging from customer satisfaction to social campaign analysis in multilingual societies. Advances in this...
was abstracted from the available data. It may include the abstraction of redundant data, unwanted symbols, white spaces, numbers, etc. The pre-processed data was utilized for extracting the features so that it was utilized for the calculation of the polarity . The classification would be done ...