CAJ | 학술논문

针对如何高效地发现农业舆情话题，提出了一种基于叙词表的舆情话题发现算法。该算法首先基于《农业叙词表》和综合性词表及网络新词构建叙词词典，作为中文分词软件的词典；然后运用 TF －IDF 计算特征词的权值，选取前 P 个特征词表示文本，并基于叙词间的关系计算词语相似度；最后，以叙词为节点构建无向图，通过对无向图聚类实现网络热点话题的发现。分析结果表明，该算法的最小识别代价为0．3534，算法运行效率相比传统算法较高。
침대여하고효지발현농업여정화제，제출료일충기우서사표적여정화제발현산법。해산법수선기우《농업서사표》화종합성사표급망락신사구건서사사전，작위중문분사연건적사전；연후운용 TF －IDF 계산특정사적권치，선취전 P 개특정사표시문본，병기우서사간적관계계산사어상사도；최후，이서사위절점구건무향도，통과대무향도취류실현망락열점화제적발현。분석결과표명，해산법적최소식별대개위0．3534，산법운행효솔상비전통산법교고。
For efficient detection of agriculture public opinion topic from massive information,a network topic detection algorithm based on thesaurus was given in this paper.Firstly,based on Agriculture Comprehen-sive Thesauruses and network new words,a thesaurus dictionary was built as the dictionary of Chinese word software;then the weight of feature words were caculated by TF -IDF,and several feature words were selected as represent text,the words similarity was computed combining with the relationship of thesaurus;finally,the thesaurus were taken as nodes to build an undirected graph,and the network hot topic detection was realized through the undirected graph clustering.The analysis results showed that the minimum algorithm cost of this method was 0.3534,its algorithm efficiency was higher than that of traditional algorithm.