Attribute-Value Extraction: The case of a Real Estate Observatory

Authors

Keywords:

Real Estate Observatory, Natural Language Processing, Information Extraction, Attribute Value Extraction

Abstract

Structured information is a valuable resource in information systems construction. The process of structuring unstructured data can be automated, but since machines can’t directly process natural language texts, NLP techniques are required. This work aims to evaluate different approaches to perform attribute-value extraction in real estate descriptions, in the context of the construction of a real estate observatory for the Province of Buenos Aires. The performance of each model is measured using precision, recall and F1-score with a partial matching approach.

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Published

2024-09-19

Issue

Vol. 10 No. 1 (2024): ASAID – Argentine Symposium on Artificial Intelligence and Big Data

Section

ASAID - Argentine Symposium on Artificial Intelligence and Data Science

License

Copyright (c) 2024 Luciana Tanevitch, Alejandro Fernández, Juan Pablo Del Río, Diego Torres

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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How to Cite

Tanevitch, L., Fernández, A., Del Río, J. P., & Torres, D. (2024). Attribute-Value Extraction: The case of a Real Estate Observatory. JAIIO, Jornadas Argentinas De Informática, 10(1), 181-194. https://revistas.unlp.edu.ar/JAIIO/article/view/17910