Overview of Rest-Mex at IberLEF 2021: Recommendation System for Text Mexican Tourism

Miguel A. Alvarez-Carmona, Ramón Aranda, Samuel Arce-Cardenas, Daniel Fajardo-Delgado, Rafael Guerrero-Rodriguez, Adrian Pastor Lopez-Monroy, J. Martínez-Miranda, Humberto Pérez Espinosa, Ansel Y. Rodríguez González
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引用次数: 36

Abstract

This paper presents the framework and results from the Rest-Mex track at IberLEF 2021. This track considered two tasks: Recommendation System and Sentiment Analysis, using texts from Mexican touristic places. The Recommendation System task consists in predicting the degree of satisfaction that a tourist may have when recommending a destination of Nayarit, Mexico, based on places visited by the tourists and their opinions. On the other hand, the Sentiment Analysis task predicts the polarity of an opinion issued by a tourist who traveled to the most representative places in Guanajuato, Mexico. For both tasks, we have built new corpora considering Spanish opinions from the TripAdvisor website. This paper compares and discusses the results of the participants for both tasks.
Rest-Mex在IberLEF 2021的概述:文本墨西哥旅游推荐系统
本文介绍了IberLEF 2021上Rest-Mex轨道的框架和结果。这条赛道考虑了两个任务:推荐系统和情感分析,使用来自墨西哥旅游地点的文本。推荐系统任务包括根据游客去过的地方和他们的意见,预测游客在推荐墨西哥纳亚里特的目的地时可能具有的满意度。另一方面,情绪分析任务预测了一位游客在墨西哥瓜纳华托最具代表性的地方旅行后发表的意见的极性。对于这两个任务,我们都建立了新的语料库,考虑了来自TripAdvisor网站的西班牙语意见。本文比较和讨论了两项任务的参与者的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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