Question Answering via Question-to-Question Mapping Tait Larson Johnson Gong Josh Daniel

Overview QA systems on the web currently are popular Common QA systems extract facts from the web, match natural language questions to facts Our approach Take pre-answered questions, and match questions to questions Hopefully useful because of the vast amount of pre-answered questions available on the web Google answers Yahoo answers Lawguru.com FAQs Do this via several NLP techniques, primarily focused around query expansion using Wordnet and language model

Query Expansion POS tagging – preprocess Search through domain of semantically similar sentences Goal: Generate phrases that will identify semantically equivalent questions in our corpus Semantic expansion Language Model for pruning Prune incorrect word sense Trained on question repository “Can I get into Stanford?” -> “Butt I get into Stanford?” Phrase Extraction

Information Retrieval Different from traditional IR Bigrams Index Query No stop words No stemming Why? These choice emphasize semantic structure of question

Results Us vs Yahoo Metric - Mean Reciprocal Rank Test questions from “unresolved” Yahoo questions Metric - Mean Reciprocal Rank We only index questions, Yahoo indexes answers also

Example Results A sharp pain in the center of the chest breastbone area? Keep getting a throbbing pain in the middle of my rib cage . any idea what it could be? Do Bush baked beans give you gas Do baked beans make you fart???? yes/no? Why i sweat and how can i stop this problem How can I stop sweating? I sweat more when it’s cold…