Co-word analysis is a method for tracing developments in a scientific discipline on the basis of texts. Often, keywords are used but other source materials, such as title words, are also used. I would prefer longer strings of text, e.g. abstracts, but I don't know if that is feasible. There is a lot of literature but the studies I have seen thus far tend to concentrate on interpretation rather than providing a detailed discussion of method.
n my research area related to how we can enhance learning by using datamining algorithms. In order to compare our algorithms we need a real dataTel and unfortunatly we could'nt find it.So what we find is just dataset related to ebusiness (BookCrossing, Movies,...). Can some one help us if there is any dataTel available in the net ?Ask
Latent Semantic Analysis (LSA) would allow you to compare the similarity of two abstracts; the creators have provided a rich literature discussing the method, which is based on Singular Value Decomposition. Other methods in this literature are LIWC, BEAGLE, and CASS. (I helped create CASS.)
You can start with some feature selection algorithms where you can extract the top relevant features. TF-IDF is known for this but others exist too. You can refer to my publication in TCBB in the link attached.
Article Classification of Protein-Protein Interaction Full-Text Docu...
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