本文選題：公交扒竊　切入點(diǎn)：聚類分析　出處：《華東師范大學(xué)學(xué)報(bào)(自然科學(xué)版)》2017年03期 　論文類型：期刊論文

【摘要】：提出了一種基于聚類的時(shí)空關(guān)聯(lián)規(guī)則的公交犯罪挖掘算法.針對(duì)某市一個(gè)區(qū)的110報(bào)警數(shù)據(jù)庫(kù)中的大量業(yè)務(wù)信息進(jìn)行分析.首先,通過(guò)文本挖掘技術(shù)從案情信息中提取時(shí)間、地點(diǎn)等信息,并利用高德地圖API的地理編碼服務(wù)和POI搜索功能對(duì)提取的地址信息進(jìn)行地址匹配,提取受害人上下車站點(diǎn)、乘坐公交線路等信息.其次,對(duì)提取得到的時(shí)空數(shù)據(jù)進(jìn)行歸并處理.最后,根據(jù)案發(fā)時(shí)段、季節(jié)以及是否節(jié)假日進(jìn)行聚類分析,然后在簇內(nèi)進(jìn)行時(shí)空關(guān)聯(lián)規(guī)則分析.這種挖掘方法具有以下特點(diǎn):①在聚類基礎(chǔ)上進(jìn)行關(guān)聯(lián)規(guī)則分析,減少掃描數(shù)據(jù)庫(kù)次數(shù),大大縮小數(shù)據(jù)掃描范圍,提高算法效率,更加適合海量犯罪數(shù)據(jù)的挖掘.②聚類后簇內(nèi)數(shù)據(jù)具有相似性,特征更加明顯,在此基礎(chǔ)上進(jìn)行關(guān)聯(lián)規(guī)則分析產(chǎn)生較小的頻繁項(xiàng)集,并且提取出置信度較高的規(guī)則.③考慮犯罪行為的時(shí)空特性,挖掘過(guò)程中同時(shí)考慮了案發(fā)季節(jié)、是否節(jié)假日等因素.
[Abstract]:This paper presents an algorithm of public transportation crime mining based on clustering space-time association rules. It analyzes a lot of business information in 110 alarm database of a certain city. Firstly, time is extracted from the case information by text mining technology. Location and other information, and using Amap API's geo-coding service and POI search function to match the extracted address information, extract information such as the victim's boarding and alighting station, bus route, etc. Secondly, Finally, clustering analysis is carried out according to the time of the crime, the season and whether the holiday or not. Then the time-space association rule analysis is carried out in the cluster. This mining method has the following characteristics: 1: 1 analyzes association rules on the basis of clustering, reduces the number of scanning databases, greatly reduces the scope of data scanning, and improves the efficiency of the algorithm. It is more suitable for mining large amount of crime data. 2. After clustering, the data in cluster have similarity and more obvious features. On this basis, association rule analysis produces smaller frequent itemsets. The rule of high confidence is extracted to consider the temporal and spatial characteristics of criminal behavior, and the factors such as the crime season, whether the holiday or not are considered in the mining process.
【作者單位】： 華東師范大學(xué)地理科學(xué)學(xué)院;
【基金】：國(guó)家理科基地科研訓(xùn)練及科研能力提高項(xiàng)目(J1310028)
【分類號(hào)】：D917.3;TP311.13
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本文編號(hào)：1572981