file - ChaSen - 奈良先端科学技術大学院大学

LabelsQueryQuestion TypesOs1Employees commuting by car are paid for the fuel bill.DescriptionB-Ds2How much is the monthly transport reimbursement paid for them?Os3My company pays for it with monthly prepaid cards.Os4But the bill is several thousands of dolors for a few people.WayB-Ws5How were the managers able to decrease the money spent for gas?I-Ws6If there is a good method, please tell me.Os7I need good solutions of this matter as soon as possible.Figure 3.5. Extracting Question Segments and Identifying Question Types.One report points out that the CRF provides a performance similar to that ofthe HMM with a number of cases less than that needed for the HMM in the orderof sample of 1 to one-several-tenths [172]. Taking advantage of these advances, theCRF has been used in natural language processing and bioinformatics. The CRF,however, is unable to forecast from an estimated model those input variables thatare set as conditions, it cannot be applied to a case that requires regeneration ofinstances based on a model.The model of CRF is described with a feature function defined by two randomvariables: one to represent conditions and the other to represent a random field.The following paragraphs explain the CRF based on explanations by Kashimaet.al.[172], which takes for example a case where the CRF was applied to a labelingto sequential symbols.For a set of feature function F , let the number of locations where featuref ∈ F holds for a combination (x, y) of random variables be φ f (x, y) and avector including this in its elements be Φ(x, y), where x is an input symbol forthe conditions of a model and y is a label that the model outputs. Let thesignificance of feature f be represented by θ f and a vector including θ f in its34