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In document categorization method by using similarity measures based on word vectors, it is important to determine key words to characterize each document. However, conventional methods select the key words based on their frequency or/and particular importance index such as tf-idf. In this paper, we propose a method to characterize each document by using temporal clusters of technical term usages...
In text categorization, one well-known document representation is bag-of-words. Although it is simple and popular, it ignores semantics, underlying linguistic information, and word correlations. In this paper, a new representation for text data is proposed which is called Bag-Of-Queries (BOQ). First, a taxonomy of the terms in the local vocabulary is extracted. Extracting a taxonomy is performed by...
Text clustering is a useful and inexpensive way to organize vast text repositories into meaningful topics categories. Although text clustering can be seen as an alternative to supervised text categorization, the question remains of how to determine if the resulting clusters are of sufficient quality in a real-life application. However, it is difficult to evaluate a given clustering of documents. Furthermore,...
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