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Fgram-tree: An index structure based on feature grams for string approximate search

  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationWeb-Age Information Management - 13th International Conference, WAIM 2012, Proceedings
Pages241-253
Number of pages13
DOIs
StatePublished - 2012
Event13th International Conference on Web-Age Information Management, WAIM 2012 - Harbin, China
Duration: 18 Aug 201220 Aug 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7418 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Web-Age Information Management, WAIM 2012
Country/TerritoryChina
CityHarbin
Period18/08/1220/08/12

Keywords

  • Fgram-Tree
  • index structure
  • string approximate search

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