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Matrix-Based Method for Inferring Elements in Data Attributes Using a Vector Space Model

Department of Systems Innovation, School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan
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Author to whom correspondence should be addressed.
Information 2019, 10(3), 107; https://doi.org/10.3390/info10030107
Received: 31 January 2019 / Revised: 1 March 2019 / Accepted: 2 March 2019 / Published: 8 March 2019
(This article belongs to the Special Issue MoDAT: Designing the Market of Data)
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Abstract

This article addresses the task of inferring elements in the attributes of data. Extracting data related to our interests is a challenging task. Although data on the web can be accessed through free text queries, it is difficult to obtain results that accurately correspond to user intentions because users might not express their objects of interest using exact terms (variables, outlines of data, etc.) found in the data. In other words, users do not always have sufficient knowledge of the data to formulate an effective query. Hence, we propose a method that enables the type, format, and variable elements to be inferred as attributes of data when a natural language summary of the data is provided as a free text query. To evaluate the proposed method, we used the Data Jacket’s datasets whose metadata is written in natural language. The experimental results indicate that our method outperforms those obtained from string matching and word embedding. Applications based on this study can support users who wish to retrieve or acquire new data. View Full-Text
Keywords: data jacket; variable label; metadata; natural language processing; market of data; vector space model data jacket; variable label; metadata; natural language processing; market of data; vector space model
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Hayashi, T.; Ohsawa, Y. Matrix-Based Method for Inferring Elements in Data Attributes Using a Vector Space Model. Information 2019, 10, 107.

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