Key Phrase Extraction tools

Key Phrase Extraction is used to extract most frequent words which are significant with respect to the applications. Key phrase extraction are most frequently used in search engine for advertisement. Some analysts also project Key phrase as topic/concept/short summery. Some of the tools for key phrase extractions are
1)Carrot2:- It is a great tool for key phrase extraction. It uses two algorithm STC and lingo. Lingo search complete key phrase with some other constraints key phrase. STC is kind of Suffix Trie. Lingo works better than STC. With STC, lingo it also uses TF-IDF, LSA. If you more number of related documents then carrot works great. It also provides flexibility in input. You can give input as indexed documents which are indexed from Nabble, Solr, google search desktop or you can also index yourself from XML.
2)KEA:- It is standard algorithm for Key phrase extraction. It provides provision of learning from RDF dictionary(in SKOS format). The dictionary will contains hierarchical taxonomy. It also gives options for Machine learning. It uses Weka for Machine learning. The document can be less in number but should have large in size. Right now it is plugged in GATE. If you don't  use RDF dictionary or large sized documents for training then this tool will not work well.
3)Maui:- It is basic KEA(mentioned above) tool but also gives options to boost taxonomy from Wikipedia.
4)wikiFier:- Like Maui, It also uses wikipedia to boost concept for Key phrase extraction.
5)Stanford topic Modeling tool:- The tools uses LDA for learning topic. It takes input and output in CSV format. It also provides options for Machine learning.
6)Mallet:- It is similar to Stanford, which is used for learning topic words.