Natural Language Processing: Introduction to C Language Algorithms

Natural Language Processing (NLP) is an important branch of computer science and artificial intelligence, aimed at enabling computers to understand and generate natural language. Some common NLP tasks include text classification, sentiment analysis, and named entity recognition. In this article, we will explore some basic NLP algorithms and implement them using the C language.

1. Text Preprocessing

Before applying any NLP algorithms, it is essential to preprocess the text data. This step mainly involves removing irrelevant characters, punctuation, and converting text to lowercase. Below is a simple example of text cleaning:

#include <stdio.h>
#include <string.h>
#include <ctype.h>
void preprocess_text(char *text) {
    int n = strlen(text);
    char result[n + 1];
    int j = 0;
    for (int i = 0; i < n; i++) {
        if (isalpha(text[i]) || isspace(text[i])) {
            result[j++] = tolower(text[i]);
        }
    }
    result[j] = '\0'; // Ensure the string is null-terminated
    strcpy(text, result); // Copy cleaned text back to original
}
int main() {
    char text[] = "Hello, World! This is an example Text...";
    printf("Original text: %s\n", text);
    preprocess_text(text);
    printf("Cleaned text: %s\n", text);
    return 0;
}

Implementation Explanation:

• <span>preprocess_text</span> function traverses the input string, retaining letters and spaces.
• Using <span>tolower</span> to convert letters to lowercase improves consistency for subsequent operations.

2. Tokenization

When analyzing documents, we often need to split sentences into individual words. This step is called tokenization.

#include <stdio.h>
#include <string.h>
void tokenize(char *text) {
    const char delimiter[2] = " ";
    char *token;
   /* Get the first substring */
   token = strtok(text, delimiter);
   /* Traverse remaining substrings */
   while(token != NULL) {
      printf("%s\n", token);
      token = strtok(NULL, delimiter);
   }
}
int main() {
    char text[] = "这是 一个 测试 文本";
   printf("Tokenization result:\n");
   tokenize(text);
   return 0;
}

Implementation Explanation:

• Utilizes <span>strtok</span> function to split the string by spaces, returning one word at a time until no more words can be extracted.

3. Word Frequency Count

Next, we can count the frequency of each word to understand the importance of the text content. A hash table can efficiently store and retrieve word frequencies.

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define SIZE 100
typedef struct WordCount {
    char word[50];
    int count;
} WordCount;
WordCount wc[SIZE];
int index_count = -1;
void add_word(const char* word) {
    for(int i=0;i<=index_count;i++) {
        if(strcmp(wc[i].word, word) == 0) {
            wc[i].count++;
            return;
        }
    }
    index_count++;
    strcpy(wc[index_count].word, word);
    wc[index_count].count=1;
}
void print_word_counts() {
    for(int i=0;i<=index_count;i++) {
        printf("%s: %d\n", wc[i].word,wc[i].count);
    }
}
int main() {
    char text[]="这 是 一 个 测试 测试 和 一个 示例 的 文本";
    tokenize_and_count_words(text);
    return 0;
}
// In the code, the tokenizer process needs to be implemented to correctly call add_word with each extracted word.

Implementation Explanation:

• Defines a structure <span>WordCount</span> to store each word and its corresponding count.
• Uses a simple method to check for existing words; if not found, it adds a new record and initializes the count.

Conclusion

This article introduced the basic steps of natural language processing, including data preprocessing, tokenization, and word frequency counting. These are core components of NLP theory that can help us better understand subsequent complex algorithms such as sentiment analysis or topic modeling. Mastering these foundational skills is crucial for further learning of more advanced algorithms, and we hope that such exercises will inspire readers to explore natural language processing technologies more deeply.