链接新闻跨多个流的时效性分析

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management Pub Date : 2017-11-06 DOI:10.1145/3132847.3132988

I. Mele, Seyed Ali Bahrainian, F. Crestani

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引用次数: 10

摘要

基于事件报道链接多个信息流，分析信息流的时间发布模式，是信息分析、发现有新闻价值的故事、研究事件演变和发现不可信信息源的重要任务。在本文中，我们提出了基于报道事件的新闻流交叉链接技术，目的是分析流之间的时间依赖性。我们的研究解决了两个主要问题:(1)如何将新闻流与报道事件或同一事件的演变联系起来;(2)新闻通讯社使用不同的发布平台报道相关事件的及时性。我们的方法是基于动态主题建模来检测和跟踪时间轴上的事件，并根据事件聚类新闻。我们利用基于事件的聚类来链接跨不同流的新闻，并提供两个评分功能，根据发布特定事件新闻的时效性对流进行排名。

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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Linking News across Multiple Streams for Timeliness Analysis

Linking multiple news streams based on the reported events and analyzing the streams' temporal publishing patterns are two very important tasks for information analysis, discovering newsworthy stories, studying the event evolution, and detecting untrustworthy sources of information. In this paper, we propose techniques for cross-linking news streams based on the reported events with the purpose of analyzing the temporal dependencies among streams. Our research tackles two main issues: (1) how news streams are connected as reporting an event or the evolution of the same event and (2) how timely the newswires report related events using different publishing platforms. Our approach is based on dynamic topic modeling for detecting and tracking events over the timeline and on clustering news according to the events. We leverage the event-based clustering to link news across different streams and present two scoring functions for ranking the streams based on their timeliness in publishing news about a specific event.

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来源期刊

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

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