Graph-Based Approach for Cross Domain Text Linking

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• 关键词：Text graph ; Cross domain text ; Text linking ; Semantic similarity
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9461
• 期：1
• 页码：151-160
• 全文大小：810 KB
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• 作者单位：Yu Hu (19)
  Tiezheng Nie (19)
  Derong Shen (19)
  Yue Kou (19)
  
  19. College of Information Science and Engineering, Northeastern University, Shenyang, China
  
• 丛书名：Web Technologies and Applications
• ISBN：978-3-319-28121-6
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Comprehensive analysis of multi-domain texts has generated an important effect on text mining. Although the objects described by these multi-domain texts belong to different fields, they sometimes are overlapped partially; and linking these texts fragments which are overlapped or complementary is a necessary step for many tasks, such as entity resolution, information retrieval and text clustering. Previous works for computing text similarity mainly focus on string-based, corpus-based and knowledge-based approaches. However cross-domain texts exhibit very special features compared to texts in the same domain: (1) entity ambiguity, texts from different domains may contain various references to the same entity; (2) content skewness, cross domain texts are overlapped partially. In this paper, we propose a novel fine-grained approach based on text graph for evaluating the semantic similarity of cross-domain texts to link the similar parts. The experiment results show that our approach gives an effective solution to discover the semantic relationship between cross domain text fragments.