Geographical classification of documents using evidence from Wikipedia

Rafael Odon de Alencar, C. Davis, Marcos André Gonçalves
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引用次数: 30

Abstract

Obtaining or approximating a geographic location for search results often motivates users to include place names and other geography-related terms in their queries. Previous work shows that queries that include geography-related terms correspond to a significant share of the users' demand. Therefore, it is important to recognize the association of documents to places in order to adequately respond to such queries. This paper describes strategies for text classification into geography-related categories, using evidence extracted from Wikipedia. We use terms that correspond to entry titles and the connections between entries in Wikipedia's graph to establish a semantic network from which classification features are generated. Results of experiments using a news data-set, classified over Brazilian states, show that such terms constitute valid evidence for the geographical classification of documents, and demonstrate the potential of this technique for text classification.
使用维基百科证据的文件地理分类
获取或近似搜索结果的地理位置通常会促使用户在查询中包含地名和其他与地理相关的术语。先前的研究表明,包含地理相关术语的查询与用户需求的很大一部分相对应。因此,为了充分响应此类查询,识别文档与位置的关联非常重要。本文描述了使用从维基百科中提取的证据将文本分类为地理相关类别的策略。我们使用条目标题对应的术语和维基百科图中条目之间的连接来建立一个语义网络,从中生成分类特征。使用巴西各州分类的新闻数据集的实验结果表明,这些术语构成了文档地理分类的有效证据,并展示了该技术在文本分类方面的潜力。
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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