With the instantaneous growth of text information, retrieving domain-oriented information from the text data has a broad range of applications in Information Retrieval and Natural language Processing. Thematic keywords give a compressed representation of the text. Usually, Domain Identification plays a significant role in Machine Translation, Text Summarization, Question Answering, Information Extraction, and Sentiment Analysis. In this paper, we proposed the Multichannel LSTM-CNN methodology for Technical Domain Identification for Telugu. This architecture was used and evaluated in the context of the ICON shared task TechDOfication 2020 (task h), and our system got 69.9% of the F1 score on the test dataset and 90.01% on the validation set.

中文翻译：

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用于泰卢固语技术域识别的多通道LSTM-CNN

随着文本信息的瞬时增长，从文本数据中检索面向领域的信息在信息检索和自然语言处理中具有广泛的应用。主题关键字给出了文本的压缩表示形式。通常，域识别在机器翻译，文本摘要，问题解答，信息提取和情感分析中起着重要作用。在本文中，我们提出了用于泰卢固语技术域识别的多通道LSTM-CNN方法。在ICON共享任务TechDOfication 2020（任务h）的上下文中使用和评估了此体系结构，我们的系统在测试数据集上的F1得分为69.9％，在验证集上为90.01％。