A text search engine might be the right tool for this. Text search engines do recommendations. Lucene uses TF/IDF (and other distance algorithms). TF/IDF is basically cosine similarity. http://lucene.apache.org/solr/
When you do a text search in newspaper articles for, say, "yoga", the TF/IDF algorithm implements essentially this: every newspaper article has a term vector. You create a newspaper article term vector that has only one word, and find the nearest other term vectors by cosine similarity. On Mon, Jul 23, 2012 at 7:03 AM, Alexander Aristov <[email protected]> wrote: > People > > i need your suggestion. I want to build a recommendation (item based) > system but I need to use text files for data model. > > Is it possible to use texts for preferences and find similar items based on > terms? > > Best Regards > Alexander Aristov -- Lance Norskog [email protected]
