随着时间的推移建模文本数据-招聘的例子

Jakob Jelencic
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引用次数: 0

摘要

随着时间的推移对多语言文本数据进行建模是一项具有挑战性的任务。本博士专注于特定领域的短到中长度时间戳文本数据的语义表示。我们以招聘广告为例对所提出的方法进行了评估,其中我们对IT职位的需求进行建模。更具体地说,我们解决了以下三个问题:统一多语言文本数据的表示;聚类相似文本数据;使用提出的语义表示来建模和预测未来的工作需求。这项工作从一个问题陈述开始,然后是对所建议的方法和方法的描述,最后是对第一个结果的概述和正在进行的研究的总结。
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Modeling Text Data Over Time - Example on Job Postings
Modelling multilingual text data over time is a challenging task. This PhD is focused on semantic representation of domain specific short to mid length time stamped textual data. The proposed method is evaluated on the example of job postings, where we are modeling demand on IT jobs. More specifically, we addresses the following three problems: unifying the representation of multilingual text data; clustering similar textual data; using the proposed semantic representation to model and predict future demand of jobs. This works starts with a problem statement, followed by a description of the proposed approach and methodology and is concluded with an overview of the first results and summary of the ongoing research.
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