A graph structured text field index based on word fragments

Kropp, D.; Walch, Georg

doi:10.1016/0306-4573(81)90050-9

Cited by 12 publications

(1 citation statement)

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“…The idea can be extended by allowing each IJ-th entry to point to a further set of twenty-six pointers, thus providing access to a dictionary via its initial trigram, and so on. The idea of using prefix substrings underlies the text field index described by Kropp and Walch [47]; Colombo and Rush have suggested the use of the least-frequent n-gram in a word, whether at the front or not, for reducing search times [48]; and n-grams can replace words in hash-coding procedures [49]. Finally, n-grams can be employed for partial-match searching thus providing a rapid way of searching a text string in response to a query word.…”

Section: Implementation Of N-gram Methodsmentioning

confidence: 99%

Applications of n‐grams in textual information systems

Robertson

Willett

1998

Journal of Documentation

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This paper provides an introduction to the use of n-grams in textual information systems, where an n-gram is a string of n, usually adjacent, characters extracted from a section of continuous text. Applications that can be implemented efficiently and effectively using sets of ngrams include spelling error detection and correction, query expansion, information retrieval with serial, inverted and signature files, dictionary look-up, text compression, and language identification.

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Section: Implementation Of N-gram Methodsmentioning

confidence: 99%

Applications of n‐grams in textual information systems

Robertson

Willett

1998

Journal of Documentation

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On the minimum vocabulary problem

Chandrasekharan

Radhakrishnan

Iyengar

1987

J. Am. Soc. Inf. Sci.

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The "minimum vocabulary problem" for a dictionary has applications in indexing and other domains of information retrieval. A simple directed-graph model of a dictionary results in a linear-time algorithm for this problem. Since it is known that many minimum vocabularies can exist for a dictionary, a computationally useful criterion for finding a "desirable minimum vocabulary" is suggested and an O(lV13) algorithm is outlined, where /VI is the number of words in the dictionary, duplicates eliminated. Furthermore, some enrichments to the model and the computational intractability of a variant called the l-lexicon problem are discussed. Directions for further work are indicated.

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A note about information science research

Salton

1985

J. Am. Soc. Inf. Sci.

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A graph structured text field index based on word fragments

Cited by 12 publications

References 5 publications

Applications of n‐grams in textual information systems

Applications of n‐grams in textual information systems

On the minimum vocabulary problem

A note about information science research

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