Entropy 2016, 18(6), 235; https://doi.org/10.3390/e18060235
A PUT-Based Approach to Automatically Extracting Quantities and Generating Final Answers for Numerical Attributes
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School of Information Science & Technology, Dalian Maritime University, Dalian 116026, China
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Department of Mathematics, Dalian Maritime University, Dalian 116026, China
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School of Computer Science and Technology, Shandong Institute of Business and Technology, Yantai 264005, China
*
Author to whom correspondence should be addressed.
Academic Editor: Andreas Holzinger
Received: 14 January 2016 / Revised: 12 June 2016 / Accepted: 12 June 2016 / Published: 22 June 2016
(This article belongs to the Special Issue Machine Learning and Entropy: Discover Unknown Unknowns in Complex Data Sets)
Abstract
Automatically extracting quantities and generating final answers for numerical attributes is very useful in many occasions, including question answering, image processing, human-computer interaction, etc. A common approach is to learn linguistics templates or wrappers and employ some algorithm or model to generate a final answer. However, building linguistics templates or wrappers is a tough task for builders. In addition, linguistics templates or wrappers are domain-dependent. To make the builder escape from building linguistics templates or wrappers, we propose a new approach to final answer generation based on Predicates-Units Table (PUT), a mini domain-independent knowledge base. It is deserved to point out that, in the following cases, quantities are not represented well. Quantities are absent of units. Quantities are perhaps wrong for a given question. Even if all of them are represented well, their units are perhaps inconsistent. These cases have a strong impact on final answer solving. One thousand nine hundred twenty-six real queries are employed to test the proposed method, and the experimental results show that the average correctness ratio of our approach is 87.1%. View Full-Text
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MDPI and ACS Style
Liu, Y.; Wang, L.; Chen, R.; Song, Y.; Cai, Y. A PUT-Based Approach to Automatically Extracting Quantities and Generating Final Answers for Numerical Attributes. Entropy 2016, 18, 235.
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