Journal of the American Society for Information Science · 2000 · 31 citations · 19 references
ComputingAstronomyComputer ScienceDatabasesInformation RetrievalNatural Language ProcessingDocument ClusteringInformation ExtractionText ClusteringText MiningText Similarity AnalysisVariant DetectionApproximate MatchingBibliographic MetadataRetrievalSimilarity DetectionSpelling Variation AnalysisString SearchingTransliteration ErrorsVariant Forms
As more online databases are integrated into digital libraries, the issue of quality control of the data becomes increasingly important, especially as it relates to the effective retrieval of information. Authority work, the need to discover and reconcile variant forms of strings in bibliographic entries, will become more critical in the future. Spelling variants, misspellings, and transliteration differences will all increase the difficulty of retrieving information. We investigate a number of approximate string matching techniques that have traditionally been used to help with this problem. We then introduce the notion of approximate word matching and show how it can be used to improve detection and categorization of variant forms. We demonstrate the utility of these approaches using data from the Astrophysics Data System and show how we can reduce the human effort involved in the creation of authority files.
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Algorithms for Clustering Data
Warren S. Sarle, Anil K. Jain, Richard C. Dubes · Technometrics · 1990 · 7.8K citations
Tian Zhang, Raghu Ramakrishnan, Miron Livny · 1996 · 3.9K citations
The String-to-String Correction Problem
Robert A. Wagner, Michael J. Fischer · Journal of the ACM · 1974 · 3.1K citations · Full text
Algorithms on strings, trees, and sequences
Dan Gusfield · 1997 · 1.7K citations