Arabic text clustering technique to improve information retrieval

2022 ◽  
Author(s):  
Ahmed H. Aliwy ◽  
Kadhim B. S. Aljanabi ◽  
Huda A. Alameen
Keyword(s):  
Information Retrieval ◽  
Text Clustering ◽  
Arabic Text ◽  
Clustering Technique

Arabic text clustering using improved clustering algorithms with dimensionality reduction

2018 ◽  
Vol 22 (S2) ◽  
pp. 4535-4549 ◽  
Author(s):  
Arun Kumar Sangaiah ◽  
Ahmed E. Fakhry ◽  
Mohamed Abdel-Basset ◽  
Ibrahim El-henawy
Keyword(s):  
Dimensionality Reduction ◽  
Clustering Algorithms ◽  
Text Clustering ◽  
Arabic Text

scholarly journals IMPROVING STUDENTS’ WRITING ABILITY IN DESCRIPTIVE TEXT THROUGH CLUSTERING TECHNIQUE AT TENTH GRADE of MA MA’ARIF ROUDHOTUT THOLIBIN METRO

2021 ◽  
pp. 19-28
Author(s):  
Desi Dwi Suryani ◽  
Anindya Muhti Apriliani
Keyword(s):  
Action Research ◽  
Learning Process ◽  
Text Clustering ◽  
Collaborative Action Research ◽  
Writing Ability ◽  
Clustering Technique ◽  
Collaborative Action ◽  
The Third ◽  
Tenth Grade ◽  
Academic Year

The objective of this research was to improve the students’ writing ability in descriptive text through clustering technique at the tenth grade of MA Ma’arif Roudhotut Tholibin Metro in academic year 2018/2019. This research was conducted at tenth grade in second semester at MA Ma’arif Roudhotut Tholibin Metro in academic year 2017/2018. The design of this research was classroom action research (CAR). This research was applied collaborative action research, this research was done in two cycle. It  is done with; planning, acting, observation and reflecting. In collecting data, the writer uses; test,observation and questionnaire. the application of the clustering technique could improve the students’ writing ability in descriptive text. Based on the results of the observation obtained the students more understanding to make descriptive sentences, and make the descriptive sentences into a descriptive text. The activity make the student become interested to describe the pictures or object, students more active and more anthusiasm in the writing learning process. Then, in Cycle 1 students passed is 15 (60%). In cycle 2 students passes the KKM (80%). Was improved 20% in cycle 2. By this number, the researcher concludes that the minimum target of success, that is 70% of the students in a class, has been achieved in cycle 2, and from the third data we can conclude it was prove that clustering technique can positively improve the students’ writing ability in descriptive text at tenth grade of MA Ma’arif Roudhotut Tholibin Metro in academic year of 2018/2019   Keyword : Improve Student’s Writing, Descriptive Text, Clustering technique.

scholarly journals The Automated VSMs to Categorize Arabic Text Data Sets

2014 ◽  
Vol 13 (1) ◽  
pp. 4074-4081
Author(s):  
Mamoun Suleiman Al Rababaa ◽  
Essam Said Hanandeh
Keyword(s):  
Data Mining ◽  
Information Retrieval ◽  
Vector Space ◽  
Text Categorization ◽  
Experimental Results ◽  
Data Sets ◽  
Arabic Text ◽  
Text Data ◽  
Evaluation Measures ◽  
Vector Space Models

Text Categorization is one of the most important tasks in information retrieval and data mining. This paper aims at investigating different variations of vector space models (VSMs) using KNN algorithm. we used 242 Arabic abstract documents that were used by (Hmeidi & Kanaan, 1997). The bases of our comparison are the most popular text evaluation measures; we use Recall measure, Precision measure, and F1 measure. The Experimental results against the Saudi data sets reveal that Cosine outperformed over of the Dice and Jaccard coefficients.

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