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In natural languages, compound words play an important role and their automatically extraction is very helpful in information retrieval, information extraction and text classification. We introduce a semi-supervised Chinese compound extraction approach based on HMM using bootstrapping in this paper. First, we define a set of tags BEMI {beginning, end, middle, independence}, which means the position...
This paper is to introduce an algorithm to cluster Chinese short texts for mining web topics based on Chinese chunks. Aiming at the characteristics of Chinese short texts, the algorithm employs N-gram feature extraction to capture Chinese chunks from texts, which reflect the text semantic structure and character dependency. Then RPCL algorithm is applied to realizing text clustering with high precision,...
Pattern-based clustering is widely applied in bioinformatics and biomedical Recently, mining high quality pattern-based clusters has become an important research direction. However, the existing methods were neither efficient in large data set nor precise at measuring the quality of clusters. These problems have greatly limited the methods' application in large data set. This paper proposes a new...
At present, it is difficult to handle unexpected exceptions in collaborative design. Ad-hoc methods are important ones, but how to utilize the expert experience efficiently, especially, store those in structured format and not to lose any information and interact under more user-friendly interface during handling exceptions, seem a mission impossible. Aiming at those, we proposed a question answering...
Finding the co-location patterns for spatial data is a challenging problem in spatial databases. While previous work focused on the discovery of co-location patterns for categorical data, we present a novel method that finds co-location patterns in spatial continuous data. Our algorithm mines the co-location patterns for continuous data by using a multi-layer index and neighbor domain set which resembles...
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