Added 2 features: word segment and number conversion - #264
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Mar 18, 2021
| import java.util.regex.Matcher; | ||
| import java.util.regex.Pattern; | ||
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| public class NumberTextConverter { |
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Add small doc, what it does exactly.
| public class NumberTextConverter { | ||
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| private TurkishMorphology morphology; | ||
| private String patternToFind = "(\\s\\d+\\s(buçuk)\\s)|(\\s(bir|iki|üç|dört|beş|altı|yedi|sekiz|dokuz|on|yirmi|otuz|kırk|elli|atmış|altmış|yetmiş|seksen|doksan|yüz|bin|milyon|milyar)\\s(buçuk)\\s)"; |
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| public NumberTextConverter(TurkishMorphology morphology) { | ||
| this.morphology = morphology; | ||
| this.halfNumberPatternT2N = Pattern.compile(patternToFind); |
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Can be static final defined as a class parameter. No need to initialize it here.
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| public class NumberTextConverter { | ||
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| private TurkishMorphology morphology; |
| this.halfNumberPatternT2N = Pattern.compile(patternToFind); | ||
| } | ||
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| public String replaceTextualNumberWithNumerically(String sentence) { |
| String[] split = matchedPart.split(" "); | ||
| String newString = ""; | ||
| if(split.length > 1) { | ||
| Double bucukNumber = 0.0; |
| return resultText; | ||
| } | ||
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| private String convertNumberListToNumericalString(String sentence, List<List<String>> numbers){ |
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This is rather complex, I will check later. If you add some tests, it is fine.
| import zemberek.morphology.TurkishMorphology; | ||
| import zemberek.normalization.NumberTextConverter; | ||
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| public class NumberConversion { |
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In examples, prefer command like names. Like "ConvertNumbers"
| import java.io.IOException; | ||
| import java.util.List; | ||
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| public class WordSegment { |
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"SegmentConnectedWords" or such.
| import zemberek.morphology.TurkishMorphology; | ||
| import zemberek.morphology.analysis.WordAnalysis; | ||
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| public class WordSegmenter { |
Owner
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Add small doc. To class or public methods. If you add some tests it is fine, I will check algortihm when I have time.
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Word segmenter: it uses dfs algorithm to find parts of string. It depends on Lexicon and word generation.
Number conversion: it uses morphology and disambiguation to find POS and detect numeric values for conversion.