An Order-Based Taxonomy for Text Similarity

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 107)


Text similarity is a common and basic issue to consider in many fields. This paper proposes a new order-based taxonomy for text similarity. Based on the different consideration on the order of text comparison unit, we classify text similarities into three categories: order-sensitive similarity, order-insensitive similarity, and order-semi-sensitive similarity. For order-sensitive similarity, each text is considered as a string of items, and text matching is carried out item by item as a pairwise alignment process. For order-insensitive similarity, each text is considered as a set of distinct items, and only item co-occurrence is considered during comparison. For order-semi-sensitive similarity, block of items with dynamically determined length is used as comparison unit, and only local order (the item order within each block) is preserved during matching. The taxonomy presented in this paper provides us an insight into the text similarity issue in an order perspective, which could be beneficial in understanding and developing this basic element in many disciplines.


Text similarity Text similarity taxonomy Order-sensitive similarity Order-insensitive similarity Order-semi-sensitive similarity Text matching Information retrieval 



This work is supported by National Natural Science Fund of China (No. 60905026, 71071141), Specialized Research Fund for the Doctoral Program of Higher Education of China (No. 20093326120004), Natural Science Fund of Zhejiang Province (No. Y1091164, Z1091224), and Zhejiang Science and Technology Plan Project (No. 2010C33016).


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© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.College of Computer Science and Information EngineeringZhejiang Gongshang UniversityHangzhouChina

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