Bushra Mahdi Hassan Al-Hashimi

In computer science, retrieving Arabic information has become a major research topic. Searching and retrieving knowledge-based information from databases is known as information retrieval (IR). However, the influence of the stop word removal part has a high impact on the retrieved Arabic text. In order to demonstrate the effect of stop words in Arabic text, we used one of the most commonly used techniques, the Jaccard technique, in this paper. We used the Jaccard technique in two ways, the first with Arabic stop words and the second way without stop words. In the experiments, we collected property Arabic datasets manually. The Arabic information retrieval system showed promising results for Arabic texts in similarity between documents and texts. It gave higher accuracy while removing stop words compared to texts containing stop words.

Iris recognition is a biometric technique that uses iris pattern information to detect person identification. Initially, the system find out the boundary of the pupil and iris. Then, Circular Hough transform used to find out the center of both pupil and iris in order to crop iris part from the eye image. After that, Daugman’s Rubber Sheet model utilized for performing the normalizing step. Then, features extracted based on Legendre moment and Local Quantized. Several orders value with many region of iris have been used to get best value, which satisfied the highest recognition rate. Matching was performed by City Block Distance. The simulation was carried out using samples from CASIA.v4-Interval database, the main tool for programming is MATLAB .

The title of the research is " INFORMATION RETRIEVAL SCHEME VIA SIMILARITY TECHNIQUE"

research link : https://thescipub.com/abstract/10.3844/jcssp.2019.1734.1745