A Method of Passage-Based Document Retrieval in Question Answering System
Man-Hung Jong, Chong-Han Ri, Hyok-Chol Choe, Chol-Jun Hwang

TL;DR
This paper introduces a passage-based document retrieval method for question answering systems that uses a proximity-aware scoring function to select the most relevant documents, demonstrating effectiveness in Korean QA systems.
Contribution
It presents a novel evaluation function considering term proximity for improved document retrieval in question answering systems.
Findings
Effective retrieval of relevant documents in Korean QA systems
Proximity-based scoring improves document relevance
Method outperforms previous retrieval approaches
Abstract
We propose a method for using the scoring values of passages to effectively retrieve documents in a Question Answering system. For this, we suggest evaluation function that considers proximity between each question terms in passage. And using this evaluation function , we extract a documents which involves scoring values in the highest collection, as a suitable document for question. The proposed method is very effective in document retrieval of Korean question answering system.
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Service-Oriented Architecture and Web Services
