Question Answering for Alzheimer Disease Using Information Retrieval

Sanmitra Bhattacharya, Luca Toldo
2012 Conference and Labs of the Evaluation Forum  
With the tremendous growth of biomedical literature and data, it's no longer feasible for researchers to manually sift through this information for answering questions on specific topics. The "Machine Reading of Biomedical Texts about Alzheimer Disease" task of CLEF QA4MRE encouraged the development of systems that can automatically find answers to questions on Alzheimer disease. To this end, we developed several information retrieval(IR) and semantic web-based strategies. Our best performing
more » ... rategy used a combination of query processing followed by IR on the background corpus, distributed by the organizers, to find correct answers. Using our systems, the highest cumulative and individual c@1 scores achieved were 0.47 and 0.66 respectively.
dblp:conf/clef/BhattacharyaT12 fatcat:py7wiseyxndqxfgwrbw4qahfny