TWinner: understanding news queries with geo-content using Twitter
TWinner: understanding news queries with geo-content using Twitter
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TWinner：使用 Twitter 理解带有地理内容的新闻查询
DOI：
10.1145/1722080.1722093
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发表时间：
2010
影响因子：
1.3
通讯作者：
L. Khan
中科院分区：
文献类型：
--
作者：
Satyen Abrol;L. Khan
在当前的世界场景中，搜索引擎战争变得比以往任何时候都更加激烈，每个搜索引擎都有必要实现用户查询的意图，以便能够为他提供更相关的搜索结果。在各种类别的搜索查询中，主要部分由具有新闻意图的搜索查询构成。看到社交媒体用户的巨大增长，媒体的时空性质可以证明是一个非常有用的工具，以提高搜索质量。在我们的工作中，我们研究了这样一个工具的发展，结合社会媒体在提高网络搜索的质量和预测用户是否正在寻找新闻或没有。我们超越了以前的研究，挖掘Twitter消息，为它们分配权重，并确定可以添加到搜索查询中的关键字，以作为现有搜索引擎算法的指针，向它表明用户正在寻找新闻。我们进行了一系列的实验，并显示的影响，双胞胎的结果。
In the present world scenario, where the search engines wars are becoming fiercer than ever, it becomes necessary for each search engine to realize the intent of the user query to be able to provide him with more relevant search results. Amongst the various categories of search queries, a major portion is constituted by those having news intent. Seeing the tremendous growth of social media users, the spatial-temporal nature of the media can prove to be a very useful tool to improve the search quality. In our work we examine the development of such a tool that combines social media in improving the quality of web search and predicting whether the user is looking for news or not. We go one step beyond the previous research by mining Twitter messages, assigning weights to them and determining keywords that can be added to the search query to act as pointers to the existing search engine algorithms suggesting to it that the user is looking for news. We conduct a series of experiments and show the impact that TWinner has on the results.