The scope of harnessing information science has been experienced in personalized decision support systems. This involves minimizing the volume of information and making deductions, such as in the case of Amazon's recommendation system. Traditional recommendation systems are becoming outdated and inadequate in meeting user requirements and technological trends. New recommendation systems like contextual, group, and social recommendation have been discovered. These systems have been investigated and analyzed using nature ...
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The scope of harnessing information science has been experienced in personalized decision support systems. This involves minimizing the volume of information and making deductions, such as in the case of Amazon's recommendation system. Traditional recommendation systems are becoming outdated and inadequate in meeting user requirements and technological trends. New recommendation systems like contextual, group, and social recommendation have been discovered. These systems have been investigated and analyzed using nature-inspired algorithms, evolutionary algorithms, swarm intelligence algorithms, and machine learning techniques to provide more precise personalized recommendations. A community-based filtering algorithm is proposed as well as an innovative hybrid intelligent algorithm to handle non-erroneous recommendations in a context-aware framework and address threats from intruders using optimization techniques and.The work aims to provide efficient solutions to problems faced by users, including sparsity, novelty, precise recommendation, and optimum decision-making solutions. The proposed models have been extensively experimented with and show superior learning mechanisms.
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Add this copy of Developing Hybrid Intelligence Based Recommender System to cart. $82.78, like new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2023 by LAP Lambert Academic Publishing.
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Fine. Trade paperback (US). Glued binding. 236 p. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Developing Hybrid Intelligence Based Recommender System to cart. $83.60, new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2023 by LAP Lambert Academic Publishing.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Trade paperback (US). Glued binding. 236 p. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
