Research on the Association of Mobile Social Network Users Privacy Information Based on Big Data Analysis

The issue of privacy protection for mobile social networks is a frontier topic in the field of social network applications.The existing researches on user privacy protection in mobile social network mainly focus on privacy preserving data publishing and access control.There is little research on the association of user privacy information,so it is not easy to design personalized privacy protection strategy,but also increase the complexity of user privacy settings.Therefore,this paper concentrates on the association of user privacy information taking big data analysis tools,so as to provide data support for personalized privacy protection strategy design.

Data mining-based analysis of acupoint selection patterns for chronic hepatitis B infection

Background:The purpose of this study was to identify the characteristics and principles of acupoints applied for treating chronic hepatitis B infection.Methods:The published clinical studies on acupuncture for the treatment of chronic hepatitis B infection were gathered from various databases,including SinoMed,Chongqing Vip,China National Knowledge Infrastructure,Wanfang,the Cochrane Library,PubMed,Web of Science and Embase.Excel 2019 was utilized to establish a database of acupuncture prescriptions and conduct statistics on the frequency,meridian application,distribution and specific points,as well as SPSS Modeler 18.0 and SPSS Statistics 26.0 to conduct association rule analysis and cluster analysis to investigate the characteristics and patterns of acupoint selection.Results:A total of 42 studies containing 47 acupoints were included,with a total frequency of 286 acupoints.The top five acupoints used were Zusanli(ST36),Ganshu(BL18),Yanglingquan(GB34),Sanyinjiao(SP6)and Taichong(LR3),and the most commonly used meridians was the Bladder Meridian of Foot-Taiyang.The majority of acupuncture points are located in the lower limbs,back,and lumbar regions,with a significant percentage of them being Five-Shu acupoints.The strongest acupoint combination identified was Zusanli(ST36)–Ganshu(BL18),in addition to which 13 association rules and 4 valid clusters were obtained.Conclusion:Zusanli(ST36)–Ganshu(BL18)could be considered a relatively reasonable prescription for treating chronic hepatitis B infection in clinical practice.However,further high-quality studies are needed.

Finding Main Causes of Elevator Accidents via Multi-Dimensional Association Rule in Edge Computing Environment

In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.

An Object Extraction Model Using Association Rules and Dependence Analysis

Extracting objects from legacy systems is a basic step in system's object orientation to improve the maintainability and understandability of the systems. A new object extraction model using association rules and dependence analysis is proposed. In this model data are classified by association rules and the corresponding operations are partitioned by dependence analysis.

SEQUENTIAL ALGORITHM FOR MULTISENSOR PROBABILISTIC DATA ASSOCIATION

Based upon a multisensor sequential processing filter, the target states in a3D Cartesian system are projected into the measurement space of each sensor to extend thejoint probabilistic data association (JPDA) algorithm into the multisensor tracking systemsconsisting of heterogeneous sensors for the data association.

A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.

Painting image browser applying an associate-rule-aware multidimensional data visualization technique

Exploration of artworks is enjoyable but often time consuming.For example,it is not always easy to discover the favorite types of unknown painting works.It is not also always easy to explore unpopular painting works which looks similar to painting works created by famous artists.This paper presents a painting image browser which assists the explorative discovery of user-interested painting works.The presented browser applies a new multidimensional data visualization technique that highlights particular ranges of particular numeric values based on association rules to suggest cues to find favorite painting images.This study assumes a large number of painting images are provided where categorical information(e.g.,names of artists,created year)is assigned to the images.The presented system firstly calculates the feature values of the images as a preprocessing step.Then the browser visualizes the multidimensional feature values as a heatmap and highlights association rules discovered from the relationships between the feature values and categorical information.This mechanism enables users to explore favorite painting images or painting images that look similar to famous painting works.Our case study and user evaluation demonstrates the effectiveness of the presented image browser.

A New Hybrid Algorithm for Association Rule Mining

HA （hashing array）, a new algorithm, for mining frequent itemsets of large database is proposed. It employs a structure hash array, ltemArray （ ） to store the information of database and then uses it instead of database in later iteration. By this improvement, only twice scanning of the whole database is necessary, thereby the computational cost can be reduced significantly. To overcome the performance bottleneck of frequent 2-itemsets mining, a modified algorithm of HA, DHA （directaddressing hashing and array） is proposed, which combines HA with direct-addressing hashing technique. The new hybrid algorithm, DHA, not only overcomes the performance bottleneck but also inherits the advantages of HA. Extensive simulations are conducted in this paper to evaluate the performance of the proposed new algorithm, and the results prove the new algorithm is more efficient and reasonable.

Photometric solution and period analysis of the contact binary system AH Cnc

Photometric observations of AH Cnc, a W UMa-type system in the open cluster M67, were car- fled out by using the 50BIN telescope. About 100h of time-series/3- and V-band data were taken, based on which eight new times of light minima were determined. By applying the Wilson-Devinney method, the light curves were modeled and a revised photometric solution of the binary system was derived. We con- firmed that AH Cnc is a deep contact （f = 51%）, low mass-ratio （q - 0.156） system. Adopting the distance modulus derived from study of the host cluster, we have re-calculated the physical parameters of the binary system, namely the masses and radii. The masses and radii of the two components were estimated to be respectively 1.188（4-0.061） Me, 1.332（4-0.063） RQ for the primary component and 0.185（4-0.032） Me, 0.592（4-0.051） Re for the secondary. By adding the newly derived minimum timings to all the available data, the period variations of AH Cnc were studied. This shows that the orbital period of the binary is con- tinuously increasing at a rate of dp/dt = 4.29 x 10-10 d yr-1. In addition to the long-term period increase, a cyclic variation with a period of 35.26 yr was determined, which could be attributed to an unresolved tertiary component of the system.

基于SQL Server Analysis Service(SSAS)的土地地类关系空间数据挖掘

基于SQL Server Analysis Services(简称SSAS)提供的Microsoft关联规则挖掘算法和事务数据挖掘功能,通过利用Arc GIS软件、空间数据库引擎Arc SDE和数据库SQL Server软件,提出了一种新的土地地类关系挖掘实现方案。首先结合空间数据挖掘(Spatial Data Mining,SDM)相关技术方法,以土地利用数据库为基础,实现空间数据提取;然后通过空间关联操作将空间信息转化为事务,最后在SSAS中创建多维数据集,完成相关数据挖掘任务。基于某市实例土地利用数据库,采用该方法探测相邻地类间的隐含关系,通过建立相邻地类图斑空间关联规则挖掘模型,设置不同的参数,得到了一系列比较实用合理的关联规则,通过实践证明了这种方案的有效性。

Identifying Association Rules among Drugs in Prescription of a Single Drugstore Using Apriori Method

These days, health care systems such as pharmacies and drugstores normally produce high volumes of data. Consequently, utilizing data mining methods in health care systems has become a conventional process. In this research, Apriori algorithm has been applied to perform data mining using the data obtained from the prescriptions ordered within a pharmacy. Ten association rules were achieved from the assigned pharmaceutical drugs in those prescriptions using the aforementioned Apriori algorithm. The accuracy of these rules is also manually studied and reviewed by a physician. Among these association rules, Vitamin D and Calcium pills are the most interrelated medications, and Omeprazole and Metronidazole rankd second in terms of association. The results of this study provide useful feedback information about associations among drugs.

Analysis of novel coronavirus pneumonia treatment with Chinese herbal compound

Objective: To analyze the prescription law of TCM compound in the treatment of new coronavirus pneumonia, and provides reference for the clinical treatment of new coronavirus pneumonia. Methods: Collected Collected 24 novel coronavirus pneumonia related diagnostic and therapeutic plans issued by the National Health Council and the Chinese medicine authority from January 26, 2020 to March 8th ,the filtered solution involved in the formula, establishing database of traditional Chinese medicine compound prescription for the treatment of new crown pneumonia, the frequency of using frequency analysis methods of analysis and clustering analysis and association rules analysis to sort out data mining analysis of traditional Chinese medicine compound. Results: In this study, a total of 159 TCM compounds were included in the treatment of new crown pneumonia from the country and 23 provinces, municipalities and autonomous regions, involving 189 TCM compounds. A total of 62 high-frequency traditional Chinese medicines (frequency ≥ 11) were obtained, mainly including licorice, almond, ephedra, gypsum, Poria cocos, Huoxiang, etc The drug types are mainly heat-clearing drugs, vacuous drugs, moisture-curing drugs, and surfactant drugs. The main effect of the medicine was warm, cold, lukewarm and flat, the main effect of the medicine was bitter and bitter, and the main effect of the medicine was the lung, stomach and spleen. Cluster analysis results according to the performance of traditional Chinese medicine treatment of new crown pneumonia high frequency drugs into 7 classes;Association rule analysis results in 29 common drug pairs. Conclusion: In the treatment of pneumonia caused by new coronavirus infection with traditional Chinese medicine, the following characteristics are presented: the number of times of supplementing qi and Yin is more than that of attacking evil and maintaining health;The method of dispersing and solving the attack of wet, beneficial, wet, permeable and wet medicine fully embodies a variety of ways to drive away evil;In terms of drugs, heat-clearing drugs, deficiency drugs, dampness drugs and surface drugs are the main ones, highlighting that the basic treatment method is to dissolve dampness and detoxify, and replenish qi and Yin. In summary, this study can provide reference for guiding clinical drug use and developing new drugs.

Intra-set correlation analysis of medical records of thyroid cancer treated by traditional Chinese medicine Master ZHOU Zhongying

Objective Based on intra-set correlation analysis, this paper deconstructs the clinical medical records of traditional Chinese medicine(TCM) Master ZHOU Zhongying in treating thyroid cancer, and analyzes the experience in “mechanism-syndrome-medicine-prescription” for thyroid cancer.Methods Through Medcase data processing platform, based on Frequent Pattern(FP)-Growth enhanced correlation analysis algorithm, the medical records of Professor ZHOU Zhongying for the treatment of thyroid cancer from June 1, 2001 to February 28, 2015 were analyzed within the set.Results This study involved 43 medical records, 43 patients, and 167 visits. After processing intra-set correlations, 28 groups of highly correlated symptoms, 21 groups of highly correlated tongue images, 10 groups of highly correlated pulse conditions, 28 groups of highly correlated pathogenesis, 34 groups of highly correlated herbs, and 26 groups of highly correlated western medicine diagnosis were selected. Professor ZHOU Zhongying treats thyroid cancer according to syndrome differentiation. Symptoms with more association rules included neck swelling, neck pain, cough, and dry mouth;tongue images with more association rules included dark purple tongue, dark red tongue, and fissured tongue;pulse conditions with more association rules were wiry pulse, thready pulse, small pulse, and slippery pulse;the pathogenesis with more association rules was phlegm and blood stasis, damp-heat accumulation,and impairment of both Qi and Yin;herbs with more association rules were Chaihu(Bupleuri Radix), Zeqi(Sun Euphoribiae Herb), and Tiandong(Asparagi Radix);western medicine diagnosis with more association rules included thyroid cancer, insomnia, and chronic gastritis.Conclusion Thyroid cancer mostly presents as deficiency in origin and excess in manifestations. The basic pathogenesis is phlegm and blood stasis, damp-heat accumulation, and impairment of both Qi and Yin, which are closely related to liver, kidney, and spleen. Professor ZHOU Zhongying adopts both attack and supplement approaches as the general treatment principle, with a strong emphasis on regulating Qi and relieving depression, eliminating phlegm and resolving stagnation, eliminating dampness and turbidity, clearing fire and destroying poison, moistening dryness and softening hard mass, invigorating Qi and nourishing Yin, and paying attention to nourishing liver and kidney, invigorating spleen and stomach,while protecting the heart and lungs.

Using adjacency matrix to explore remarkable associations in big and small mineral data

Data exploration,usually the first step in data analysis,is a useful method to tackle challenges caused by big geoscience data.It conducts quick analysis of data,investigates the patterns,and generates/refines research questions to guide advanced statistics and machine learning algorithms.The background of this work is the open mineral data provided by several sources,and the focus is different types of associations in mineral properties and occurrences.Researchers in mineralogy have been applying different techniques for exploring such associations.Although the explored associations can lead to new scientific insights that contribute to crystallography,mineralogy,and geochemistry,the exploration process is often daunting due to the wide range and complexity of factors involved.In this study,our purpose is implementing a visualization tool based on the adjacency matrix for a variety of datasets and testing its utility for quick exploration of association patterns in mineral data.Algorithms,software packages,and use cases have been developed to process a variety of mineral data.The results demonstrate the efficiency of adjacency matrix in real-world usage.All the developed works of this study are open source and open access.

基于数据驱动贝叶斯网络的化工事故风险分析

为减少化工厂风险分析中的主观干预,基于关联规则和贝叶斯网络构建1种数据驱动风险分析模型。该模型涵盖3个任务项,分别为数据集项、关联规则驱动项和贝叶斯网络风险评估项。首先,收集事故报告和事故因素构建事故数据库;其次,将事故数据导入Apriori算法,并根据关联规则的因素相关性确定贝叶斯网络和条件概率表结构;然后,基于事故因素出现频率计算先验概率和条件概率,并采用Fussel-Vesely计算事故因素的敏感度;最后,收集94起危险化学品中毒窒息事故实例,运用数据驱动风险分析模型评估事故因素的影响大小。研究结果可为减少和避免化工事故提供一定参考,有助于提高相关企业的整体安全水平。

基于古籍挖掘的糖尿病中医食疗方调制规律研究

目的 探究糖尿病中医食疗方的调制规律,为糖尿病的临床辨证施食和食疗研究提供参考。方法 收集《中医方剂大辞典》《中医食疗方全录》《中国药膳大辞典》三本纸版古籍中收载的糖尿病食疗方,提取方名、组成、剂型等信息,应用SPSS 26.0进行频数分析及聚类分析,采用SPSS Modeler 18.0开展食物配伍关联分析。结果 共纳入食疗方264首,涉及191种食物。古代糖尿病中医食疗方多用补虚类(47.91%)食药物质及保健食品药材,清热类(11.84%)次之;多以平性(36.65%)、温性(31.41%)为主;味多甘味(55.38%);归经则以脾经(18.99%)、肾经(17.51%)、胃经(16.46%)、肺经(15.40%)居多;汤剂为常见剂型(32.58%);五谷类食物使用较多(25.25%);其主治证型以气阴亏虚(32.07%)为主。结论 古代医家重视由调治中焦入手,灵活应用中医食疗方调治糖尿病,讲究补虚辅以清热利湿,善于理气和中祛湿化浊,妙用“温”品,遵循辨证原则,选材多味,组方多样,为临床进行中医食疗干预糖尿病提供了有益借鉴与思路启发。

序列稀疏自回归方法及其在美股做空数据分析上的应用

采用序列稀疏回归的思路来处理向量自回归模型,并设计适用于大规模时间序列数据分析的序列稀疏自回归方法。研究表明:从因子角度刻画向量自回归模型可以有效地将稀疏矩阵估计问题分解成稀疏奇异向量的估计问题,从而极大地提高了计算效率。以1523家美股上市公司1973年1月—2014年12月的做空数据为例,利用此方法探索公司之间的大规模做空关联网络。研究发现:此方法可以有效地恢复股票做空份额(即某一公司的空头股份数量)与股票收益率之间隐藏的关联网络,对于股票风险溢价研究具有一定启发意义。

基于数据挖掘的中医药治疗原发性干燥综合征燥湿互结证的用药规律研究

目的:总结北京中医药大学东方医院风湿科研究团队治疗原发性干燥综合征燥湿互结证的用药规律。方法:筛选2018年1月至2022年12月原发性干燥综合征燥湿互结证患者的病历资料,使用Excel软件建立数据库并进行统计,采用Modeler 18.0软件进行关联规则和复杂网络分析,联合Cytoscape软件对结果进行可视化。采用SPSS 20.0软件进行聚类分析。结果:共纳入处方139首,涉及188味中药,使用频次≥25次的中药共34味。筛选出药物关联组合73条,复杂网络分析得到核心中药组合丹参-青蒿-石斛-白芍,共得到8个聚类组合。结论:原发性干燥综合征燥湿互结证临证用药以清化湿热、祛瘀生津为法,根据“湿”“热”“燥”“瘀”的不同程度加减化裁,为干燥综合征的临床用药提供思路及参考。

基于《中医方剂大辞典》的雷丸组方用药规律分析

目的 基于数据挖掘方法探究《中医方剂大辞典》中雷丸的组方用药规律。方法 以《中医方剂大辞典》为信息源,梳理含雷丸的方剂,构建雷丸方药数据库;采用文献分析和数据挖掘方法,探讨雷丸的增效减毒及其方剂主治病症类型、药物配伍情况;利用关联规则分析探寻其在常见病中的配伍特点;使用皮尔逊相关性分析发掘药-证的相关性,总结其用药规律。结果 含有雷丸方剂的剂型主要为丸剂和散剂,高频用药为槟榔、大黄、木香等,与雷丸配伍的主要为驱虫药、泻下药及理气药等,且味多为苦、辛,归胃经、脾经。其中“槟榔-雷丸”出现的药对配伍频数最高,其次是“大黄-雷丸”“木香-雷丸”;雷丸方剂的主治病症为虫积的频数最高,其次为疳证、积滞等。皮尔逊相关性分析结果表明,治疗虫积配伍槟榔、木香、使君子、芜荑、鹤虱等;治疗疳证配伍胡黄连、黄连、青皮等;治疗积滞配伍神曲、陈皮、牵牛子、三棱等。结论 雷丸与槟榔等配伍可加强杀虫消积的功效;与胡黄连、大黄等配伍可增加泻下攻积的作用,以上可能会引起轻微的胃肠道不良反应;与陈皮、神曲等配伍可保护胃黏膜,减轻胃肠不良反应。但雷丸毒性物质基础研究等未见报道,仍需深入研究,为雷丸临床应用提供更确切的基础。

关联规则在高职院校教学监控中的应用研究

随着国家对高等职业教育的大力扶持,高职院校提高教育教学质量,增强社会服务能力,是学校持续发展的有效途径之一。科学有效的教学监控评价机制可以提升人才培养质量,该文中利用关联分析算法和数据挖掘工具(SPSS Modeler)进行教学评价。首先对学院的教学评价数据进行关联分析,之后对教学评价关联分析的数据进行优化,根据优化的数据进一步完善学院教学评价机制,提出切实能够改进教育教学质量的措施和方法,保障日常教育教学质量,提高人才培养质量。