Abstract
String approximate search is widely used in many areas. Indexing is no doubt a feasible way for efficient approximate string searching. However, the existing index structures have a common weakness that they do not obey the nature of the index which is a function by mapping different data to different index items, similar data to similar index items, in order to query easily. In this paper, we propose a new type of string indexing structure called Fgram-Tree, which is based on feature grams to build itself and filter strings. It obeys the two maps by placing similar strings into the same node, different strings into different nodes that could greatly improve the efficiency of index. Our index is able to support for different types of search. Compared to other index, it provides high scalability and fast response time.
This paper was partially supported by NGFR 973 grant 2012CB316200 and NSFC grant 61003046, 6111113089. Doctoral Fund of Ministry of Education of China (No. 20102302120054).
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© 2012 Springer-Verlag Berlin Heidelberg
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Tong, X., Wang, H. (2012). Fgram-Tree: An Index Structure Based on Feature Grams for String Approximate Search. In: Gao, H., Lim, L., Wang, W., Li, C., Chen, L. (eds) Web-Age Information Management. WAIM 2012. Lecture Notes in Computer Science, vol 7418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32281-5_24
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DOI: https://doi.org/10.1007/978-3-642-32281-5_24
Publisher Name: Springer, Berlin, Heidelberg
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