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Semi-supervised learning and active learning are important techniques to build more accurate model while labeled data are scarce. The objective of this paper is combining both to effectively relieve user labor for multi-class annotation. We propose a novel graph-based active semi-supervised learning framework which aim at efficiently learning a multi-class model with minimal human labor. In particular,...
This paper proposes an effective forecasting framework for the Oilfield Class-A materials, which take a large scale of proportion in the total purchasing cost. Based on the ARIMA model in time series analysis method, the dynamic forecasting framework is constructed to make short-time price prediction for Class-A materials in Oilfield, which only needs a small sample set to obtain high prediction accuracy...
According to the monitoring and analysis of chloroform in the water distribution network in a northern city of China, the variations of chloroform in the water distribution network and the major influence factors were studied. Using principle component analysis method, the prediction model which including 9 water quality indexes was established to predict the concentration of chloroform and the average...
With the flourish of the Internet, online review mining has attracted a lot of attention from the research community. However, compared to various well-studied sentiment analysis and opinion summarization problems, less effort has been made to analyze the quality of online reviews. The objective of this paper is to fill in this gap by automatically evaluating the "helpfulness" of reviews...
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