Search strategy of focused crawler based on Bloch quantumevolutionary algorithm
基于量子行为进化算法的聚焦爬虫搜索策略

According to the single value evaluation focused crawler search strategy has the topic drift problem, and make full use of the intelligence of the Bloch quantum evolutionary algorithmBQEA, this paper proposed a new algorithm of focused crawler. The algorithm integrated Web distribution on the Internet fully, used the advantages of two types of evaluation criteria of the immediate value and the future value adjusted to the proportion of two standards online in the integrated value, according to focused crawler search on the actual process. The experimental result by simulation show that, compared with the search strategy of a single value, the BQEA obtains a higher recall rate, and precision rate and can solve the existing problems with certain self-adaptive.