Research on the Recommendation Algorithm Based on 0-1 Knapsack Problem

Wenrong Jiang
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引用次数: 1

Abstract

Knapsack Problem is a NP complete Problem of combinatorial optimization. The problem can be described as: given a set of items, each item has its own weight and value. Within the limited total weight, how can we choose to maximize the total value of the item? Similar problems often occur in the business, combinatorial mathematics, cryptography, and applied mathematics, and other fields, and this problem can be described as a crucial question, namely "under the premise of not more than the total weight W, can achieve total value V?". This article with a algorithm design, example, grouping solving 0-1 knapsack problem algorithm, analysis the advantages and disadvantages of each algorithm, and the solution algorithm based on knapsack problem, to put forward a recommendation algorithm can be applied in song recommended, advertising, news, etc.
基于0-1背包问题的推荐算法研究
背包问题是一个NP完全组合优化问题。这个问题可以描述为:给定一组物品,每个物品都有自己的重量和价值。在有限的总重量下,我们如何选择使物品的总价值最大化?类似的问题经常出现在商业、组合数学、密码学以及应用数学等领域,而这个问题可以用一个至关重要的问题来形容,即“在不超过总权重W的前提下,能否实现总价值V?”本文结合算法设计、实例、分组求解0-1背包问题的算法,分析了每种算法的优缺点,并对基于背包问题的算法进行求解,提出了一种可以应用于歌曲推荐、广告、新闻等方面的推荐算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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