Hello openNLP Developers I would like to contribute a component which relies on openNLP, and gives search engineers a simple relevance verification tool which relies on machine learning of syntactic parse trees.
The value for search engineers community is that they dont have to be familiar with NLP to use syntactic generalization component, which does parsing/chunking by openNLP and then graph-based learning for relevance assessment (proposed component). One of the expected usage scenario is that a search library like lucene is used, and this component would accept / reject irrelevant search results (according to the proposed syntactic generalization measure). This code has been deployed commercially over last 2 years at datran.com and zvents.com and is serving > 20 mln users monthly. There is a number of publications on this project, including http://portal.acm.org/citation.cfm?id=1881190 http://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS11/paper/view/2573 Regards Boris
