Mohammad Amir Sharif

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The distribution of the number of items liked by users plays an important role in designing recommender systems. In case of implicit feedback we rarely get some clicking events compared to large item based e-commerce sites, where preference information is not so rare. In this paper we present a novel hybrid recommendation system based on clustering of items(More)
JPEG (Joint Photographic Experts Group) is one of the most popular compression standard in the field of still image compression. The compression ratio of lossless methods (e.g., Huffman, Arithmetic, LZW) is not high enough for image and video compression, especially when the distribution of pixel values is relatively flat. The lossless encoding schemes can(More)
The distribution of the amount of preference information across customers is not same in every domain of recommendation problems. It is necessary to treat each user differently based on their available preference information. On the other hand, graph structure can provide better representation of user-item preference information. By exploiting graph(More)
Internet has become primary medium for information access, commerce in today's globalized world and almost every information is available in the Internet either in the native language of the user or in a non-native language. Therefore, it becomes easier to use another author's contents from the Internet without proper citation or reference and this tendency(More)
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