Towards Recommending Interesting Content in News Archives

Towards Recommending Interesting Content in News Archives
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推荐新闻档案中有趣的内容

DOI:
10.1007/978-3-030-04257-8_13
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发表时间:
2018
期刊:
The 20th International Conference on Asia-pacific Digital Libraries (ICADL 2018)
影响因子:
--
通讯作者:
Adam Jatowt
Adam Jatowt
中科院分区:
--
文献类型:
--
作者:
I-Chen Hung;Michael Faeber;Adam Jatowt

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最近,许多档案新闻文章集已提供给广大公众。然而,这样的集合通常很大,使得用户难以找到他们感兴趣的内容。此外,存档的新闻文章往往被普通用户视为具有相当弱的吸引力和过时或无趣。在本文中,我们提出了从新闻档案中发现有趣内容的任务,并介绍了两种简单的方法。我们的方法推荐有趣的内容,通过比较过去写的信息和一个从现在。
Recently, many archival news article collections have been made available to wide public. However, such collections are typically large, making it difficult for users to find content they would be interested in. Furthermore, archived news articles tend to be perceived by ordinary users as having rather weak attractiveness and being obsolete or uninteresting. In this paper, we propose the task of finding interesting content from news archives and introduce two simple methods for it. Our approach recommends interesting content by comparing the information written in the past with the one from the present.
DOI: 10.1109/slt.2012.6424268
发表时间: 2012-12
期刊: 2012 IEEE Spoken Language Technology Workshop (SLT)
影响因子: --
作者:
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通讯作者: Yun-Nung (Vivian) Chen;Florian Metze
DOI: --
发表时间: 2016
期刊: --
影响因子: --
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DOI: --
发表时间: 2002
期刊:
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