This article presents a state of the art and a comparison of unsupervised methods for automatic keywords extraction from documents. We evaluate several methods from the literature on two sets of documents by comparing the keywords extracted and those initially associated with documents. We found that the best method (the one that retrieves keywords the closest to the authors’ keywords) is based...

A hierarchical framework is proposed to address the issues of modeling different type of words in keyword spotting (KWS). Keyword models are built at various levels according to the availability of training set resources for each individual word. The proposed approach improves the performance of KWS even when no training speech is available for the keywords. It also suggests an easier way to co...

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Incremental clustering is a very useful approach to organize dynamic text collections. Due to the time/space restrictions for incremental clustering, the textual documents must be preprocessed to maintain only their most important information. Statistical keyword extraction methods from single documents are useful in this scenario. However, different statistical methods have different assumptio...

Determination of the characteristic CP-violating quantity sin(2β) should be the central goal of a B-meson factory in its first-round experiments. Except the gold-plated channels B d → ψK S and ψK L , three other types of B d decays to CP eigenstates can also serve for the extraction of sin(2β) in the standard model: (a) the CP-forbidden

In this paper, we propose a novel approach for keyword extraction. Different from previous keyword extraction methods, which identify keywords based on the document alone, this approach introduces Wikipedia knowledge and document genre to extract keywords from the document. Keyword extraction is accomplished by a classification model utilizing not only traditional word based features but also f...