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  • Evaluation and Enhancement of Arabic Text Retrieval Models
Presenter Name: Ayat Elnahas
Lecture Date:11/15/2021 11:00:00 AM
lecture Topic: Master thesis
Department: Informatics
Lecture Title:
Evaluation and Enhancement of Arabic Text Retrieval Models
Lecture Summary:

Due to the rapid growth of the amount of Arabic documents uploaded to the Internet, information retrieval has become a very important task. Information retrieval systems aim to retrieve the relevant documents; from a collection of documents; as a response of an input user query. The queries and stored documents are unstructured data.
This lecture discusses the query expansion process using the word embedding concept. The continuous-bag-of-words (CBOW), Skip-Gram, and the amalgamation of both are also analyzed, implemented, and evaluated.
Three machine learning approaches for classifying text and/or documents are also discussed. The approaches are decision tree (DT), Naïve Bayes (NB), and support vector machine (SVM). Moreover, a set of feature selection methods: term-weighting, Gini Index, Information Gain, Chi-Square, and the amalgamation of them.

Presenter Profile: Click here
Lecture Slides: Download
Lecture Link:
keywords:
informatics #NLP #Arabic #text_retrieval #semantic #word_embedding #classification

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