A graph based method for Arabic document indexing

Bazzi, Mohamed Salim El; Mammass, Driss; Zaki, Taher; Ennaji, Abdellatif

doi:10.1109/setit.2016.7939885

Cited by 7 publications

(1 citation statement)

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“…It is a way of retrieving all the terms characterizing a document. Document indexing is an important step in the text mining process, because it determines how the knowledge contained in the documents is represented [1]. It takes place each time a document is added to the corpus.…”

Section: Introductionmentioning

confidence: 99%

Toward a Complex System for Context Discovery to Index Arabic Documents

Bazzi¹

2018

JCP

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Text indexing aims to take the full advantage of textual data to help intelligent programs to make relevant decisions. In order to explore a large amount of textual documents, and to disclose semantic information hidden in unstructured documents, like texts, an effective indexation system is required. In this paper, we propose a new approach for indexing Arabic texts. Based on the semantic proximity and taking into account the contexts contained in each document, our method is denoted contextual indexing. Several algorithms are used for keywords extraction, each of them emphasizes some criterion. However, we target the most descriptive keywords for each document. We also propose a new approach for document modeling. We compared the results obtained using our method with those obtained by an indexation system based on a standard statistical method. The experimental results demonstrate the performance of our approach.

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Section: Introductionmentioning

confidence: 99%