FB-KEA: A Feature-Based Keyword Extraction Algorithm for Improving Hit Performance

In the age of Internet, people usually use search engines by giving keywords to find the information they need. For content providers, the reference performance of a given content is majorly determined by the set of keywords. In literature, there have been many studies proposed algorithms for finding keywords. However, most of them cannot reflect important properties, such as the expert’s knowledge and trends. This work proposes a novel keyword extraction algorithm, called FB-KEA, which extracts the keywords based on the features including semantic, expert experience as well as trend of hot search. Experimental results show that the proposed FB-KEA has significant improvements in terms of hit ratio, as compared with traditional methods.