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In this paper an off-line Arabic/Farsi handwritten recognition Algorithm on a subset of Farsi name is proposed. In this system, There is no sub-word segmentation phase. Script database includes 3300 images of 30 Farsi common names. The features are wavelet coefficients extracted from smoothed word image profiles in four standard directions. The Centers of(More)
Color quantization is a technique for processing and reduction colors in image. The purposes of color quantization are displaying images on limited hardware, reduction use of storage media and accelerating image sending time. In this paper a hybrid algorithm of GA and Particle Swarm Optimization algorithms with FCM algorithm is proposed. Finally, some of(More)
Data sparsity, that is a common problem in neighbor-based collaborative filtering domain, usually complicates the process of item recommendation. This problem is more serious in collaborative ranking domain, in which calculating the users' similarities and recommending items are based on ranking data. Some graph-based approaches have been proposed to(More)
Internet is a huge source of information. The growth of information and unstructured and semi structured nature of web information, cause some challenges for people to find their potential useful information for long-time needs. Hence, the implementation of automated tools selecting and evaluating information is necessary. Information filtering could be(More)
Neighbor-based collaborative filtering is one of the most practical recommendation approaches that is renowned because of its simplicity and explanation. However, the big limitation is its high computational complexity. It is demonstrated that clustering-based algorithms, that restrict the neighborhood space, speed up the recommendation process at the price(More)
Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art(More)
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