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Collaborative filtering (CF) techniques are used in recommender systems to provide users with specialised recommendations on social websites and in e-commerce. But they suffer from sparsity and cold start problems (CSP) and fail to interpret why they recommend a new item. A novel deep ranking weighted multihash recommender (DRWMR) system is designed to suppress sparsity and CSP. The proposed DRWMR system contains two stages: the neighbours’ formation and recommendation phases. Initially, the data is fed to the deep convolutional neural network (CNN). The significant features are extracted from CNN. The CNN contains an additional layer; the hash code is generated by minimising pairwise ranking loss and classification loss. Therefore, a weight is assigned to different hash tables and hash bits for a recommendation. Then, the similarity between users is obtained based on the weighted hammering distance; the similarity between users helps to form the neighbourhood for the active user. Finally, the rating for unknown items can be obtained by taking the weighted average rating of the neighbourhood, and a list of the top n items can be produced. The effectiveness and accuracy of the proposed DRWMR system are tested on the MovieLens 100 K dataset and compared with the existing methods. Based on the evaluation results, the proposed DRWMR system gives precision (0.16), the root mean squared error (RMSE) of 0.73 and the recall (0.08), the mean absolute error (MAE) of 0.57, and the F − 1 measure (0.101).

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Here, is the study on VMOSA of Maybelline NEW YORK. VMOSA (vision, mission, objectives, strategies and action plans) is a practical planning process. VMOSA helps an organization to achieve short term goals while keeping sight of long-term goals. Vision: in an organization to develop a strategy, first make a clear vision of future. Mission: it refers to a vision, that what an organization will actually do to meet its vision. Objectives: these are the set of instructions which are helpful to achieve the organizational vision. Strategies: strategies are set up to meet each of the objectives. Action plans: action plans are create to make each of the strategy happen. Online survey of Maybelline NEW YORK is conducted in Google form 100 respondents.