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Improving the Retrieval of Arabic Web Search Results Using Enhanced k-Means Clustering Algorithm.

Amjad F Alsuhaim1,2, Aqil M Azmi1, Muhammad Hussain1

  • 1Department of Computer Science, College of Computer & Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.

Entropy (Basel, Switzerland)
|April 30, 2021
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Summary
This summary is machine-generated.

This study introduces an enhanced k-means clustering algorithm to improve Arabic information retrieval. The new method speeds up document clustering and helps users quickly find relevant Arabic search results.

Keywords:
Arabicclustering algorithmsenhanced k-meansinformation retrievaltext miningweb search

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Area of Science:

  • Information Retrieval
  • Natural Language Processing
  • Computer Science

Background:

  • Traditional information retrieval systems struggle with ambiguous languages like Arabic due to omitted diacritics.
  • Arabic search queries often require users to manually sift through long result lists to find relevant information.
  • Ambiguity in modern Arabic writing hinders effective information retrieval.

Purpose of the Study:

  • To propose an enhanced k-means clustering algorithm for organizing Arabic search results.
  • To improve the efficiency and user experience of retrieving information in Arabic.
  • To address the challenges posed by Arabic language ambiguity in search systems.

Main Methods:

  • Utilized an enhanced k-means clustering algorithm that optimizes distance calculations for faster processing.
  • Implemented a system to cluster Arabic search results, assigning cluster labels based on the most frequent word.
  • Compared the enhanced k-means algorithm's performance against the regular k-means on stemmed and non-stemmed Arabic datasets.

Main Results:

  • The enhanced k-means algorithm demonstrated a significant reduction in execution time: 60% for stemmed data and 47% for non-stemmed data.
  • The algorithm achieved slightly improved purity in clustering compared to the standard k-means.
  • The proposed system effectively labels clusters, aiding users in topic identification.

Conclusions:

  • The enhanced k-means algorithm offers a more efficient solution for clustering Arabic search results.
  • This approach enhances the usability of information retrieval systems for Arabic language users.
  • The system facilitates quicker topic identification and navigation within search results.