Class TermSuggestionBuilder

    • Constructor Detail

      • TermSuggestionBuilder

        public TermSuggestionBuilder​(java.lang.String field)
      • TermSuggestionBuilder

        public TermSuggestionBuilder​(StreamInput in)
        Read from a stream.
    • Method Detail

      • suggestMode

        public TermSuggestionBuilder suggestMode​(TermSuggestionBuilder.SuggestMode suggestMode)
        The global suggest mode controls what suggested terms are included or controls for what suggest text tokens, terms should be suggested for. Three possible values can be specified:
        1. missing - Only suggest terms in the suggest text that aren't in the index. This is the default.
        2. popular - Only suggest terms that occur in more docs then the original suggest text term.
        3. always - Suggest any matching suggest terms based on tokens in the suggest text.
      • accuracy

        public TermSuggestionBuilder accuracy​(float accuracy)
        s how similar the suggested terms at least need to be compared to the original suggest text tokens. A value between 0 and 1 can be specified. This value will be compared to the string distance result of each candidate spelling correction.

        Default is 0.5

      • accuracy

        public float accuracy()
        Get the accuracy setting.
      • sort

        public TermSuggestionBuilder sort​(SortBy sort)
        Sets how to sort the suggest terms per suggest text token. Two possible values:
        1. score - Sort should first be based on score, then document frequency and then the term itself.
        2. frequency - Sort should first be based on document frequency, then score and then the term itself.

        What the score is depends on the suggester being used.

      • sort

        public SortBy sort()
        Get the sort setting.
      • stringDistance

        public TermSuggestionBuilder stringDistance​(TermSuggestionBuilder.StringDistanceImpl stringDistance)
        Sets what string distance implementation to use for comparing how similar suggested terms are. Five possible values can be specified:
        1. internal - This is the default and is based on damerau_levenshtein, but highly optimized for comparing string distance for terms inside the index.
        2. damerau_levenshtein - String distance algorithm based on Damerau-Levenshtein algorithm.
        3. levenshtein - String distance algorithm based on Levenshtein edit distance algorithm.
        4. jaro_winkler - String distance algorithm based on Jaro-Winkler algorithm.
        5. ngram - String distance algorithm based on character n-grams.
      • maxEdits

        public TermSuggestionBuilder maxEdits​(int maxEdits)
        Sets the maximum edit distance candidate suggestions can have in order to be considered as a suggestion. Can only be a value between 1 and 2. Any other value result in an bad request error being thrown. Defaults to 2.
      • maxEdits

        public int maxEdits()
        Get the maximum edit distance setting.
      • maxInspections

        public TermSuggestionBuilder maxInspections​(int maxInspections)
        A factor that is used to multiply with the size in order to inspect more candidate suggestions. Can improve accuracy at the cost of performance. Defaults to 5.
      • maxInspections

        public int maxInspections()
        Get the factor for inspecting more candidate suggestions setting.
      • maxTermFreq

        public TermSuggestionBuilder maxTermFreq​(float maxTermFreq)
        Sets a maximum threshold in number of documents a suggest text token can exist in order to be corrected. Can be a relative percentage number (e.g 0.4) or an absolute number to represent document frequencies. If an value higher than 1 is specified then fractional can not be specified. Defaults to 0.01.

        This can be used to exclude high frequency terms from being suggested. High frequency terms are usually spelled correctly on top of this this also improves the suggest performance.

      • maxTermFreq

        public float maxTermFreq()
        Get the maximum term frequency threshold setting.
      • prefixLength

        public TermSuggestionBuilder prefixLength​(int prefixLength)
        Sets the number of minimal prefix characters that must match in order be a candidate suggestion. Defaults to 1. Increasing this number improves suggest performance. Usually misspellings don't occur in the beginning of terms.
      • prefixLength

        public int prefixLength()
        Get the minimum prefix length that must match setting.
      • minWordLength

        public TermSuggestionBuilder minWordLength​(int minWordLength)
        The minimum length a suggest text term must have in order to be corrected. Defaults to 4.
      • minWordLength

        public int minWordLength()
        Get the minimum length of a text term to be corrected setting.
      • minDocFreq

        public TermSuggestionBuilder minDocFreq​(float minDocFreq)
        Sets a minimal threshold in number of documents a suggested term should appear in. This can be specified as an absolute number or as a relative percentage of number of documents. This can improve quality by only suggesting high frequency terms. Defaults to 0f and is not enabled. If a value higher than 1 is specified then the number cannot be fractional.
      • minDocFreq

        public float minDocFreq()
        Get the minimal threshold for the frequency of a term appearing in the document set setting.
      • getWriteableName

        public java.lang.String getWriteableName()
        Description copied from interface: NamedWriteable
        Returns the name of the writeable object