Predicting the User Intention in Web Search

Gilson dos Reis Dias Fonseca, J. Souza, E. Barrére
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Abstract

The search for information is inherent to the human being and with the popularization of computers, search systems have become the main source of obtaining knowledge. However, they do not support greater user interaction when they want to do a complex search. It is important to evaluate the user and infer information about him, to know his intention to search to increase the performance of these systems under the principles of SaL. In this paper, we propose a model for classifying the search intention using Transformers. It was used an available dataset and we obtained 97% accuracy in the validation set and 99% f-measure in the test set, achieving better results when comparing to traditional methods.
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预测网络搜索中的用户意图
对信息的搜索是人类的天性,随着计算机的普及,搜索系统已经成为获取知识的主要来源。但是,当需要进行复杂的搜索时,它们不支持更好的用户交互。重要的是评估用户并推断有关他的信息,了解他的搜索意图,以便在SaL原则下提高这些系统的性能。本文提出了一种基于transformer的搜索意图分类模型。它使用了一个可用的数据集,我们在验证集中获得了97%的准确率,在测试集中获得了99%的f-measure,与传统方法相比取得了更好的结果。
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