Multi-Field Structural Decomposition for Question Answering

04/04/2016
by   Tomasz Jurczyk, et al.
0

This paper presents a precursory yet novel approach to the question answering task using structural decomposition. Our system first generates linguistic structures such as syntactic and semantic trees from text, decomposes them into multiple fields, then indexes the terms in each field. For each question, it decomposes the question into multiple fields, measures the relevance score of each field to the indexed ones, then ranks all documents by their relevance scores and weights associated with the fields, where the weights are learned through statistical modeling. Our final model gives an absolute improvement of over 40 containing answers.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/18/2014

Cognitive Systems and Question Answering

This paper briefly characterizes the field of cognitive computing. As an...
research
02/01/2022

Research on Question Classification Methods in the Medical Field

Question classification is one of the important links in the research of...
research
12/03/2019

SemEval-2016 Task 3: Community Question Answering

This paper describes the SemEval–2016 Task 3 on Community Question Answe...
research
03/02/2022

Recent, rapid advancement in visual question answering architecture: a review

Understanding visual question answering is going to be crucial for numer...
research
07/23/2018

Question Relevance in Visual Question Answering

Free-form and open-ended Visual Question Answering systems solve the pro...
research
06/24/2018

One-shot Learning for Question-Answering in Gaokao History Challenge

Answering questions from university admission exams (Gaokao in Chinese) ...
research
06/20/2019

Hindi Question Generation Using Dependency Structures

Hindi question answering systems suffer from a lack of data. To address ...

Please sign up or login with your details

Forgot password? Click here to reset