CAJ | 학술논문

随着大数据信息技术的发展，数据在线监测和数据挖掘成为计算机信息领域研究的热点。通过对Web热点数据分割挖掘，提高信息热点追踪和Web数据分类能力。传统算法采用非结构化数据挖掘算法，无法有效对Web热点数据进行准确定位和分层挖掘。提出一种基于半结构化分割的Web热点数据挖掘算法。采用半结构化数据进行特征分割，基于优秀基因位进行差分进化，使寻优曲线不断趋于平缓，在多个节点上并行的运行比较脚本，采用半结构化分割，使得Web热点特征挖掘实现自适应寻优，得到Web热点数据的分配因子，提高了挖掘性能。仿真结果表明，该算法获得了良好的效率和精度，提高了Web热点数据挖掘的自适应寻优能力。
수착대수거신식기술적발전，수거재선감측화수거알굴성위계산궤신식영역연구적열점。통과대Web열점수거분할알굴，제고신식열점추종화Web수거분류능력。전통산법채용비결구화수거알굴산법，무법유효대Web열점수거진행준학정위화분층알굴。제출일충기우반결구화분할적Web열점수거알굴산법。채용반결구화수거진행특정분할，기우우수기인위진행차분진화，사심우곡선불단추우평완，재다개절점상병행적운행비교각본，채용반결구화분할，사득Web열점특정알굴실현자괄응심우，득도Web열점수거적분배인자，제고료알굴성능。방진결과표명，해산법획득료량호적효솔화정도，제고료Web열점수거알굴적자괄응심우능력。
With the development of big data information technology, online monitoring data and data mining has become a hot research field of computer information. The segmentation of Web hot data mining, improve the classification ability of information focus and Web data. Using the traditional algorithm of unstructured data mining algorithms, it is not valid for Web hot data for accurate positioning and layered mining. The paper proposed a mining algorithm Web hot data structured based on segmentation, feature segmentation using semi structured data, excellent genes are based on differential evolution, make the optimization curve tends to be gentle, parallel on multiple nodes running script, through the code makes the un?structured data mapped to the data block, make the data stored in the database relational data model, to get the distribution factor Web hot data, improve the mining performance.The simulation results show that the high efficiency and accuracy, it improved adaptive Web hotspot of data mining optimization ability.