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Class TableDiscreteFunction


  • public class TableDiscreteFunction
extends FuzzyAlgorithm
    Represents the fuzzy search algorithm that contains correspondences between word lengths and the number of allowed mistakes. This algorithm can be specified by a table of output values or by a step function.

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    The example demonstrates a typical usage of the class. 

     
 String indexFolder = "c:\\MyIndex\\";
 String documentsFolder = "c:\\MyDocuments\\";
 String query = "Einstein";
 Index index = new Index(indexFolder); // Creating an index in the specified folder
 index.add(documentsFolder); // Indexing documents from the specified folder
 SearchOptions options = new SearchOptions();
 options.getFuzzySearch().setEnabled(true); // Enabling the fuzzy search
 options.getFuzzySearch().setFuzzyAlgorithm(new TableDiscreteFunction(1, new Step(5, 2), new Step(8, 3))); // Creating the fuzzy search algorithm
 // This function specifies 1 as the maximum number of mistakes for words from 1 to 4 characters.
 // It specifies 2 as the maximum number of mistakes for words from 5 to 7 characters.
 // It specifies 3 as the maximum number of mistakes for words from 8 and more characters.
 SearchResult result = index.search(query, options); // Search in index

    • Constructor Detail

      • TableDiscreteFunction

        public TableDiscreteFunction(int offsetOfInputs,
                             int[] tableOfOutputs)
        Initializes a new instance of the TableDiscreteFunction class.
        Parameters:
        offsetOfInputs - The offset of the table indeces relative to the input values.
        tableOfOutputs - The table of output values.

      • TableDiscreteFunction

        public TableDiscreteFunction(int firstStepLevel,
                             Step... steps)
        Initializes a new instance of the TableDiscreteFunction class.
        Parameters:
        firstStepLevel - The level of the first step of the step function.
        steps - The next steps of the step function.

    • Method Detail

      • getSimilarityLevel

        public double getSimilarityLevel(int termLength)
        Gets a similarity level for specified term length.
        Specified by:
        getSimilarityLevel in class FuzzyAlgorithm
        Parameters:
        termLength - The term length.
        Returns:
        A similarity level.

      • getMaxMistakeCount

        public int getMaxMistakeCount(int termLength)
        Gets a maximum allowed number of mistakes for specified term length.
        Specified by:
        getMaxMistakeCount in class FuzzyAlgorithm
        Parameters:
        termLength - The term length.
        Returns:
        A maximum allowed number of mistakes.