Keyword extraction attracts much attention for its significant role in various natural language processing tasks. While some existing methods for keyword extraction have considered using single type of semantic relatedness between words or inherent attributes of words, almost all of them ignore two important issues: 1) how to fuse multiple types of semantic relations between words into a unifor...

In recent years, many private corporations and government organizations have digitized corpuses of legacy paper documents. Often, these organizations hope to take advantage of digital representations to transform costly manual tasks associated with paper archives into less-costly computer-assisted tasks. The most common approach toward automated information extraction is through inverted indexi...

This paper examines the differences between author generated keywords and automatically generated keywords in one area of scientific and technical literature. Using inverse frequency, keywords produced using both methods are examined using a maximum likelihood algorithm. By reducing the scope and size of the corpus of literature examined, this study more closely emulates the information gatheri...