Compression space high-efficiency search method based on complex network

Abstract

The invention relates to a high effect searching method for compressed space based on a complicate network, which aims at mining a core node with higher influence in a complicate network as an initiate active node, and then sequentially activating other nodes in the network according to the influence weights on the directed edge of the network, thereby furthest activating more nodes. The problem can be transformed into a problem of maximization of network overlay in the graph theory, which is proved as an NP difficulty in mathematics, and therefore, aiming to the characteristic that different parameter measurement methods only can detect a certain aspect of a complicate network in the complicated network, the invention provides a compressed space searching algorithm based on heuristic information. The compressed space searching algorithm comprises after preprocessing of common greed algorithm, hill climbing algorithm and high in-degree heuristic information algorithm, selecting three ordered optimal node sets from the global scope to be merged into a chaotic candidate node set, and adding suboptimum node sets of the three algorithms to form a candidate node universal set capable of complete enumeration in an effective time. The searching method compresses a huge, incompact original solution space with large amount of redundant information into another solution space which is concentrative, and is processible by a computer and provided with high heuristic information, thereby guaranteeing to find out a group of better solution in utmost.

Description

technical field [0001] The invention relates to the fields of social network analysis and graph theory, in particular to a complex network-based high-efficiency search method for compressed space. Background technique [0002] As more and more customers start shopping online, traditional targeted marketing methods are no longer applicable. The best marketing method is to let customers recommend and market products by themselves. Sociological findings show that users who interact frequently with each other tend to be more similar. Users who connect with each other are likely to be similar, and similar users tend to buy the same products. At present, social networking sites are very popular, such as FaceBook, Myspace, Twitter and other social networking sites are widely popular, so that online target marketing has a large amount of data resources. Due to the use of word of mouth among users, it is more efficient and faster to carry out target marketing strategies through vi...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned technologies, and provide a high-efficiency search method for compressed space based on complex networks. In complex networks, different parameters reflect the characteristics of different aspects of the network, and network coverage maximization is an NP-hard problem. , different parameter measurement methods can only examine the characteristics of a certain aspect, so the present invention proposes a heuristic information compression space search algorithm, which can find a group of better solutions as much as possible

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