A Quick Algorithm for Mining Exceptional Rules

Exceptional rules are often ignored because of their small support. However, they have high confidence, so they are useful sometimes. A new algorithm for mining exceptional rules is presented, which creates a large itemset from a relatively small database and scans the whole database only one time to generate all exceptional rules. This algorithm is proved to be quick and effective through its application in a mushroom database.

Study on prescription and medication rules of Hua Baojin for treatment of colorectal cancer based on data mining

Objective:To study the prescription and medication rule of Professor Hua Baojin in the treatment of colorectal cancer through data mining,so as to provide reference for clinical treatment of colorectal cancer. Methods:The outpatient medical records of Professor Hua Baojin from June 2015 to October 2020 in Guang’anmen Hospital,China Academy of Chinese Medical Sciences were collected. TCM Inheritance Support Platform(V2.5)was used to analyze high-frequency drugs,drug properties,flavors,channel tropism,common drug combinations,core combinations and new prescriptions. Results:A total of 500 prescriptions were included,involving 222 traditional Chinese medicines and 38 high-frequency(≥100)medicines,including Atractylodes,Poria cocos,ginger,etc. The most common medicinal properties of drugs were warm,cold and mild,and flavors were sweet,bitter and pungent,channel tropism included spleen,stomach,liver and lung meridians. 36 groups of common drug combinations and 20 association rules were obtained by data mining,and 18 core combinations and 9 new prescriptions were evolved.Conclusion:Professor Hua Baojin takes recuperating spleen and stomach as the core in the treatment of colorectal cancer,attaching importance to regulating the rise and fall of qi,adding and subtracting on the basis of Xiangsha Liujunzi Decoction,flexibly selecting the drugs of dispelling blood stasis,resolving phlegm,detoxification and loose knots,and using both cold and warm in the prescription,tonifying and reducing at the same time.

Study on the rules of TCM syndromes and Chinese herbal medicines about IgAN based on data mining

Objective:To analyze the clinical research literatures of TCM syndromes and treatment of Immunoglobulin A Nephropathy(IgAN)on data-mining technology,and explore the rules of TCM syndromes and Chinese medication.Methods:By searching the clinical literatures about TCM syndromes and treatment of IgAN had published in China Biomedical Literature Database,CNKI Database,Wanfang Database,and Chongqing Weipu Database from January 2000 to September 2019.Strictly according to the inclusion and exclusion criteria,included documents and established the databases.Applicated of statistical software for frequency analysis of TCM syndromes,Chinese herbal medicines,and analyzed the commonly used Chinese herbal medicines by factor analysis and cluster analysis.Results:292 literatures were finally included,involving 28 syndromes.A total of 479 prescriptions and 254 Chinese herbs were used.The rules of syndromes in IgA nephropathy are as follows:the syndromes are mainly composed of Qi and Yin deficiency syndrome,followed by the Spleen and kidney qi deficiency syndrome,Liver and Kidney Yin Deficiency Syndrome,Spleen and kidney yang deficiency syndrome.The blood-stasis syndrome,damp-heat syndrome and wind-heat disturbance syndrome are accompanied by other syndrome.The characteristics of traditional Chinese medicines for IgA nephropathy is mainly composed of tonic deficiency medicines,supplemented by blood-activating and stasis-eliminating medicines,heat-clearing medicines,inducing diuresis and excreting dampness medicines and astringent medicines to combine with formulas.Conclusion:Through Data-mining method systematically summarized the rules of TCM syndromes and Chinese medication in treating IgAN and provided scientific theoretical guidance for the treatment of IgAN.

Study on the medication rules of traditional Chinese medicine in the treatment of sleep disorder after stroke based on data mining

Objective:To explore the medication rule of Traditional Chinese Medicine(TCM)in the treatment of sleep disorder after stroke by using data mining technology.Methods:A computer search was used to search the electronic database of clinical literature on the treatment of sleep disorders after stroke by TCM from January 2000 to January 2021.Excel was used to establish the database,and the prescription information was described and analyzed statistically.Using IBM SPSS Modeler 18.0 software,Apriori algorithm was used for TCM association analysis,and IBM SPSS 22.0 software was used for systematic cluster analysis of high-frequency TCM.Results:A total of 67 literatures were included,covering 131 traditional Chinese medicines.The medecines with a higher frequency of sodium use include Ziziphi Spinosae Semen(Suanzaoren),Angelicae Sinensis Radix(Danggui),Ligusticum(Chuanxiong),liquorice(Gancao),Poria cocos(Fuling),and so on.From the effect point of view,deficiency-tonifying medicine,sedative medicine and blood-activating and stasis-removing medicine are commonly used.The medicinal properties are mainly cold,mild and warm.The main medicine flavor are sweet and bitter.The medicines mostly belong to the liver,heart and spleen Meridian.Thirty-three association rules were obtained for medicine pairs and medicine groups from the correlation analysis,and the core combinations were"Ziziphi Spinosae Semen(Suanzaoren)-Tuber fleeceflower stem(Yejiaoteng)","Ziziphi Spinosae Semen(Suanzaoren)-Polygala(Yuanzhi)","Ziziphi Spinosae Semen(Suanzaoren)-Cortex albiziae(Hehuanpi)"and"Angelicae Sinensis Radix(Danggui)-Radix bupleuri(Chaihu)-Radix Paeoniae Alba(Baishao)"and so on.Seven medicine aggregation groups were obtained by medicine cluster analysis.Conclusion:In the treatment of sleep disorder after stroke by TCM,the main method is to calm the heart and mind.Meanwhile,according to different syndrome types,the treatment methods of tonifying the heart and spleen,nourishing the liver and kidney,soothing the liver and softening the liver,clearing heat and resolving phlegm,nourishing the blood and promoting blood circulation are selected,which provide certain reference for clinical treatment.

A study of medication rules of traditional Chinese medicine in the treatment of pre diabetes based on data mining

Background:To summarize the concerted application and prescription rules of traditional Chinese medicine in the treatment of pre diabetes.Methods:Microsoft Excel 2010 was used to summarize the categories,nature,flavour and channel tropism of drugs.The cluster analysis of high-frequency drugs was carried out by SPSS 22.0,and the association rules of high-frequency drugs were analyzed by Apriori algorithm provided by SPSS modeler 14.0.Results:One hundred and forty-six references were included,including 153 prescriptions and 131 drugs.Their frequency of use is listed in the following order.The top 3 categories of drugs were“Tonifying,Heat-Clearing”,diuresis and“Diffusing Dampness”drugs.The top 5 drugs were Huangqi(Astragali radix),Fuling(Poria),Huanglian(Coptidis rhizoma),Shanyao(Dioscoreae rhizoma),Gegen(Puerariae lobatae radix).The top 3 channel tropism of drugs were spleen,stomach and lung.The top 3 nature of drugs were cold,warm and calm.The top 3 flavour of drugs were sweet,bitter and pungent.The cluster analysis of high-frequency drugs showed that it could be classified into 4 categories:“Benefiting Qi”for promoting production of fluid,“Clearing Heat”and“Eliminating Dampness”,“Nourishing Yin”and“Clearing Heat”,and“Invigorating Spleen”for“Diffusing Dampness”.The results of association rule analysis showed that the combination with the highest degree of confidence and support was Poria-Chenpi(Citri reticulatae pericarpium)-Banxia(Pinelliae rhizoma)-Baizhu(Atractylodis macrocephalae rhizoma)and the combination with the highest frequency was Astragali radix-Puerariae lobatae radix.Conclusion:The pre diabetes is due to deficiency.The disease location is spleen and stomach and the pathological factor is phlegm-damp,that is why benefiting qi and invigorating spleen is regarded as the key link of clinical treatment.

An Analysis of Medication Rules of Chinese Medicine for Restless Legs Syndrome Based on Data Mining

Objective: Based on data mining, to explore the medication rules of Chinese medicine for the treatment of restless legs syndrome(RLS). Methods: The CNKI, WANFANG, and VIP were taken as data sources, and "restless legs syndrome, RLS" as the key words, and "Chinese medicine, Chinese materia medica, traditional Chinese medicine(TCM), traditional Chinese and Western medicine" as sub key words, the data was extracted from the journals and literature related to the treatment of RLS by TCM from the establishment of the database to 2020, and data mining techniques(frequency analysis, cluster analysis, association rules) were used to analyze the core drugs and drug pair(group) rules. Results: A total of 87 prescriptions met the requirements of this study, involving 142 Chinese herbal medicines. The top 5 Chinese herbal medicines with a higher frequency of use were Radix Paeoniae Alba, Radix Glycyrrhizae, Radix Angelicae Sinensis, Fructus Chaenomelis and Radix Astragali seu Hedysari. The four Qi(气) of the medicine were mainly warm and neutral, the five flavors were mainly sweet, bitter, and pungent. The main channels of the meridian were mainly the liver meridian, spleen meridian and heart meridian. The medication categories were mainly tonifying deficiency herbs, blood activating and removing blood stasis herbs, and eliminating wind and dampness herbs. The association rule analysis yielded 24 Chinese medicine combinations with high support, and the hierarchical cluster analysis yielded a total of 5 clusters. Conclusion: TCM treatment of RLS is based on tonifying deficiency herbs, especially to replenish Qi and blood throughout the course of the disease, supplemented by herbs for promoting blood circulation and removing blood stasis, and herbs for eliminating wind and dampness, as well as combined with herbs for reliving superficies and herbs for calming the liver to stop the wind.

Medication Rules of Traditional Chinese Medicine for Treating Threatened Abortion in the Early Stage of Pregnancy with Subchorionic Haematoma Based on Data Mining

Objective:Using data mining technology to explore the rules of traditional Chinese medicine(TCM)in the treatment of threatened abortion in the early stage of pregnancy with sub-chorionic haematoma(SCH).Methods:Literature of TCM in the treatment of threatened abortion in the early stage of pregnancy with SCH were retrieved from CNKI,VIP,WANFANG and Pubmed,EMBASE.The literature information database was established to be used for descriptive analysis,association rule analysis and cluster analysis of relevant data.Results:A total of 100 literatures were included,involving 114 Chinese herbs.The efficacy of Chinese herbs were mainly tonic drugs,hemostatic drugs,heat-clearing drugs,dissolving blood stasis and hemostatic drugs.The medicinal properties were mostly mild and warm,and the taste of the drug was mainly sweet,bitter and pungent.The liver meridian,spleen meridian and kidney meridian were frequently used.The commonly used drug pair combination was"Xu duan(Radix dipsaci,续断)-Tusizi(Semen Cuscutae,菟丝子)",and the core combination was"Tusizi-Xu duan-Ejiao(Donkeyhide gelatin,阿胶)-Baizhu(Atractylodes macrocephala,白术)-Dangshen(Codonopsis pilosula,党参)".Commonly used drugs for removing blood stasis and hemostasis were with Sanqi(Panax notoginseng,三七),Puhuang(cattail pollen,蒲黄),and Qiancao(Radix Rubiae,茜草).Conclusion:Data mining traditional Chinese medicine for the treatment of threatened abortion in the early stage of pregnancy with SCH clinically commonly used drug efficacy,taste,meridian,commonly used drug pairs,core combination and commonly used blood stasis hemostatic drugs,has important reference significance for the treatment of threatened abortion in the early stage of pregnancy combined with SCH.

Research on the modern clinical herbal administration rules in TCM treatment of ovarian cysts based on data mining

Objective:To explore the recent 20 years' herbal administration rules in TCM treatments of ovarian cysts (OCs) based on data mining.Methods:A prescription database for ovarian cysts was established by ACCESS 2007.Importing the database into SPSS17.0 and SPSS Modeler14.1.SPSS17.0 was used for descriptive and cluster analyses,while SPSS Modeler14.1 was used for association rules analysis.Results:After screening,363 prescriptions were obtained.The 10 most frequently-used Chinese herbal medicines are Zedoaria (Rhizoma Curcumae),Poria cocos (Poria),Common buried rubber (Rhizoma Sparganii),Red peony root (Radix Paeoniae Rubra),Peach seed (Semen Persicae),Danggui (Radix Angelicae Sinensis),Chinese angelica (Ramulus Cinnamomi),Liquorice root (Radix Glycyrrhizae),Pangolin scales (Squama Manis) and Moutan cortex (Cortex Moutan Radicis);the 5 most common syndromes of OCs are qi stagnation and blood stasis,phlegm and blood stasis,uterine blood stasis,stagnation of liver qi and retention of phlegm and dampness,nearly to 54.26%;In association rules analysis,5 sets of two-herbs association rules were obtained,17 sets of three-herbs association rules were obtained,22 sets of four-herbs association rules were obtained and 4 sets of five-herbs association rules were obtained;By clustering,13 sets of core couplet medicinals were obtained.Conclusion:Medicinal herbs for promoting blood circulation to remove blood stasis,resolve hard lumps,for strengthening the spleen,eliminating phlegm,and relieving liver qi stagnation were highly used in the treatment of OCs;Herbs attributed to the Liver Meridian,the Spleen Meridian and the Heart Meridian were highly used in OCs;The compatibility of herbs for promoting blood circulation to remove blood stasis and resolve hard lumps were highly used;Guizhi Fuling Wan (GFW) was often used and combined with other herbs in the treatment of OCs.

Integrated data mining and network pharmacology to discover a novel traditional Chinese medicine prescription against diabetic retinopathy and reveal its mechanism

Background:Diabetic retinopathy(DR)is currently the leading cause of blindness in elderly individuals with diabetes.Traditional Chinese medicine(TCM)prescriptions have shown remarkable effectiveness for treating DR.This study aimed to screen a novel TCM prescription against DR from patents and elucidate its medication rule and molecular mechanism using data mining,network pharmacology,molecular docking and molecular dynamics(MD)simulation.Method:TCM prescriptions for treating DR was collected from patents and a novel TCM prescription was identified using data mining.Subsequently,the mechanism of the novel TCM prescription against DR was explored by constructing a network of core TCMs-core active ingredients-core targets-core pathways.Finally,molecular docking and MD simulation were employed to validate the findings from network pharmacology.Result:The TCMs of the collected prescriptions primarily possessed bitter and cold properties with heat-clearing and supplementing effects,attributed to the liver,lung and kidney channels.Notably,a novel TCM prescription for treating DR was identified,composed of Lycii Fructus,Chrysanthemi Flos,Astragali Radix and Angelicae Sinensis Radix.Twenty core active ingredients and ten core targets of the novel TCM prescription for treating DR were screened.Moreover,the novel TCM prescription played a crucial role for treating DR by inhibiting inflammatory response,oxidative stress,retinal pigment epithelium cell apoptosis and retinal neovascularization through various pathways,such as the AGE-RAGE signaling pathway in diabetic complications and the MAPK signaling pathway.Finally,molecular docking and MD simulation demonstrated that almost all core active ingredients exhibited satisfactory binding energies to core targets.Conclusions:This study identified a novel TCM prescription and unveiled its multi-component,multi-target and multi-pathway characteristics for treating DR.These findings provide a scientific basis and novel insights into the development of drugs for DR prevention and treatment.

Construction and Practice of Teaching Evaluation System Based on Data Mining

The teaching quality evaluation system based on data mining technology can accurately and fairly identify the core driving factors to improve teaching quality.This method adopts the analysis of big data correlation rules,including data collection and processing preparation steps,builds the data warehouse of association rules,and then generates an educational quality evaluation framework using the principle of data mining.Based on this,this paper analyzes the construction design and method of the teaching evaluation system under data mining,hoping to provide help for the improvement of the teaching evaluation system and the improvement of teaching quality.

Data Mining-Based Maintenance Management Framework of Multi-component System

Complex repairable system is composed of thousands of components.Some maintenance management and decision problems in maintenance management and decision need to classify a set of components into several classes based on data mining.Furthermore,with the complexity of industrial equipment increasing,the managers should pay more attention to the key components and carry out the lean management is very important.Therefore,the idea"customer segmentation"of"precise marketing"can be used in the maintenance management of the multi-component system.Following the idea of segmentation,the components of multicomponent systems should be subdivied into groups based on specific attributes relevant to maintenance,such as maintenance cost,mean time between failures,and failure frequency.For the target specific groups of parts,the optimal maintenance policy,health assessment and maintenance scheduling can be determined.The proposed analysis framework will be given out.In order to illustrate the effectiveness of this method,a numerical example is given out.

Hydraulic metal structure health diagnosis based on data mining technology

In conjunction with association rules for data mining, the connections between testing indices and strong and weak association rules were determined, and new derivative rules were obtained by further reasoning. Association rules were used to analyze correlation and check consistency between indices. This study shows that the judgment obtained by weak association rules or non-association rules is more accurate and more credible than that obtained by strong association rules. When the testing grades of two indices in the weak association rules are inconsistent, the testing grades of indices are more likely to be erroneous, and the mistakes are often caused by human factors. Clustering data mining technology was used to analyze the reliability of a diagnosis, or to perform health diagnosis directly. Analysis showed that the clustering results are related to the indices selected, and that if the indices selected are more significant, the characteristics of clustering results are also more significant, and the analysis or diagnosis is more credible. The indices and diagnosis analysis function produced by this study provide a necessary theoretical foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.

Mining Software Repository for Cleaning Bugs Using Data Mining Technique

Despite advances in technological complexity and efforts,software repository maintenance requires reusing the data to reduce the effort and complexity.However,increasing ambiguity,irrelevance,and bugs while extracting similar data during software development generate a large amount of data from those data that reside in repositories.Thus,there is a need for a repository mining technique for relevant and bug-free data prediction.This paper proposes a fault prediction approach using a data-mining technique to find good predictors for high-quality software.To predict errors in mining data,the Apriori algorithm was used to discover association rules by fixing confidence at more than 40%and support at least 30%.The pruning strategy was adopted based on evaluation measures.Next,the rules were extracted from three projects of different domains;the extracted rules were then combined to obtain the most popular rules based on the evaluation measure values.To evaluate the proposed approach,we conducted an experimental study to compare the proposed rules with existing ones using four different industrial projects.The evaluation showed that the results of our proposal are promising.Practitioners and developers can utilize these rules for defect prediction during early software development.

Traditional Chinese medicine Master XIONG Jibo’s medication experience in treating arthralgia syndrome through data mining

Objective This study aimed to examine and propagate the medication experience and group formula of traditional Chinese medicine(TCM)Master XIONG Jibo in diagnosing and treat-ing arthralgia syndrome(AS)through data mining.Methods Data of outpatient cases of Professor XIONG Jibo were collected from January 1,2014 to December 31,2018,along with cases recorded in A Real Famous Traditional Chinese Medicine Doctor:XIONG Jibo's Clinical Medical Record 1,which was published in December 2019.The five variables collected from the patients’data were TCM diagnostic information,TCM and western medicine diagnoses,syndrome,treatment,and prescription.A database was established for the collected data with Excel.Using the Python environment,a custom-ized modified natural language processing(NLP)model for the diagnosis and treatment of AS by Professor XIONG Jibo was established to preprocess the data and to analyze the word cloud.Frequency analysis,association rule analysis,cluster analysis,and visual analysis of AS cases were performed based on the Traditional Chinese Medicine Inheritance Computing Platform(V3.0)and RStudio(V4.0.3).Results A total of 610 medical records of Professor XIONG Jibo were collected from the case database.A total of 103 medical records were included after data screening criteria,which comprised 187 times(45 kinds)of prescriptions and 1506 times(125 kinds)of Chinese herbs.The main related meridians were the liver,spleen,and kidney meridians.The properties of Chinese herbs used most were mainly warm,flat,and cold,while the flavors of herbs were mainly bitter,pungent,and sweet.The main patterns of AS included the damp heat,phlegm stasis,and neck arthralgia.The most commonly used herbs for AS were Chuanniuxi(Cyathu-lae Radix),Huangbo(Phellodendri Chinensis Cortex),Cangzhu(Atractylodis Rhizoma),Qinjiao(Gentianae Macrophyllae Radix),Gancao(Glycyrrhizae Radix et Rhizoma),Huangqi(Astragali Radix),and Chuanxiong(Chuanxiong Rhizoma).The most common effect of the herbs was“promoting blood circulation and removing blood stasis”,followed by“supple-menting deficiency(Qi supplementing,blood supplementing,and Yang supplementing)”,and“dispelling wind and dampness”.The data were analyzed with the support≥15%and con-fidence=100%,and after de-duplication,five second-order association rules,39 third-order association rules,39 fourth-order association rules,and two fifth-order association rules were identified.The top-ranking association rules of each were“Cangzhu(Atractylodis Rhizoma)→Huangbo(Phellodendri Chinensis Cortex)”“Cangzhu(Atractylodis Rhizoma)+Chuanniuxi(Cyathulae Radix)→Huangbo(Phellodendri Chinensis Cortex)”“Chuanniuxi(Cyathulae Radix)+Danggui(Angelicae Sinensis Radix)+Gancao(Glycyrrhizae Radix et Rhizoma)→Qinjiao(Gentianae Macrophyllae Radix)”and“Chuanniuxi(Cyathulae Radix)+Danggui(Angelicae Sinensis Radix)+Gancao(Glycyrrhizae Radix et Rhizoma)+Huangbo(Phello-dendri Chinensis Cortex)→Qinjiao(Gentianae Macrophyllae Radix)”,respectively.Five clusters were obtained using cluster analysis of the top 30 herbs.The herbs were mainly dry-ing dampness,supplementing Qi,and promoting blood circulation.The main prescriptions of AS were Ermiao San(二妙散),Gegen Jianghuang San(葛根姜黄散),and Huangqi Chongteng Yin(黄芪虫藤饮).The herbs of core prescription included Cangzhu(Atractylodis Rhizoma),Chuanniuxi(Cyathulae Radix),Gancao(Glycyrrhizae Radix et Rhizoma),Huangbo(Phellodendri Chinensis Cortex),Mugua(Chaenomelis Fructus),Qinjiao(Gentianae Macro-phyllae Radix),Danggui(Angelicae Sinensis Radix),and Yiyiren(Coicis Semen).Conclusion Clearing heat and dampness,relieving collaterals and pain,and invigorating Qi and blood are the most commonly used therapies for the treatment of AS by Professor XIONG Jibo.Additionally,customized NLP model could improve the efficiency of data mining in TCM.

A study on the rule of Chinese medicine use against influenza virus based on data mining

Background:To summarize the rules of the use of traditional Chinese medicine against influenza virus in the high-quality literatures of core journals,and to provide guidance for the prevention and treatment of influenza.Methods:Excel 2010 and ancient and modern medical case cloud platform(2.5V)were used to summarize the categories,nature,flavour and channel tropism of drugs.The cluster analysis of high-frequency drugs was carried out by SPSS 22.0,and the association rules of high-frequency drugs were analyzed by Apriori algorithm provided by SPSS modeler 18.0.Results:One thousand one hundred and thirty-one articles from core journals were retrieved and 135 articles were screened out,including 109 prescriptions and 170 drugs,with a total frequency of 1,655 times.The 3 most frequently appeared herbs were Gancao(Glycyrrhizae radix et rhizoma),Jinyinhua(Lonicerae japonicae flos)and Lianqiao(Forsythiae fructus).The top 3 efficacy were“Heat-Clearing(remove heat from the body surface and inside)”drugs,drugs for“Relieving Exterior Disorder(treat fever,chills and headaches caused by pathogenic substances in the air)”,and“Phlegm Relieving Cough Antiasthmatic Medicine(relieves respiratory cough and sputum symptoms)”drugs.The top 3 nature of drugs were cold,warm and flat.The top 3 flavour of drugs were bitter,spicy and sweet.The top 5 channel tropism of drugs were“Lung”,“Stomach”,“Heart”,“Spleen”,“Liver”.Association rule yields 20 drug pairs,Jingjie(Schizonepetae herba),Forsythiae fructus,Lonicerae japonicae flos,Niubangzi(Arctii fructus),Mahuang(Ephedrae herba)and Glycyrrhizae radix et rhizoma were commonly used concerted application;four new methods were obtained by cluster analysis.Conclusion:The use of traditional Chinese medicine against influenza virus has a certain regularity,which provides an important reference value for the prevention and treatment of influenza.

Data Mining Based on Computational Intelligence

This paper combines computational intelligence tools: neural network, fuzzylogic, and genetic algorithm to develop a data mining architecture (NFGDM), which discovers patternsand represents them in understandable forms. In the NFGDM, input data arepreprocesscd byfuzzification, the preprocessed data of input variables arc then used to train a radial basisprobabilistic neural network to classify the dataset according to the classes considered, A ruleextraction technique is then applied in order to extract explicit knowledge from the trained neuralnetworks and represent it m the form of fuzzy if-then rules. In the final stage, genetic algorithmis used as a rule-pruning module to eliminate those weak rules that are still in the rule bases.Comparison with some known neural network classifier, the architecture has fast learning speed, andit is characterized by the incorporation of the possibility information into the consequents ofclassification rules in human understandable forms. The experiments show that the NFGDM is moreefficient and more robust than traditional decision tree method.

Algorithm of Intrusion Detection Based on Data Mining and Its Implementation

Intrusion detection is regarded as classification in data mining field. However instead of directly mining the classification rules, class association rules, which are then used to construct a classifier, are mined from audit logs. Some attributes in audit logs are important for detecting intrusion but their values are distributed skewedly. A relative support concept is proposed to deal with such situation. To mine class association rules effectively, an algorithms based on FP-tree is exploited. Experiment result proves that this method has better performance.

Research on law of acupoints selection for acupuncture treatment of postpartum depression based on data mining method

Objective:To obtain the rules of acupoint use and compatibility methods from RCT literature of acupunctureand moxibustion in the treatment of postpartum depression through data mining,so as to provide effective acupoints for clinical reference.Methods:a total of 557 clinical literatures on acupuncture and moxibustion in the treatment of postpartum depression were retrieved through China knowledge Network Database,Wanfang Database and Chongqing VIP Database,and 44 articles were obtained through inclusion and exclusion criteria.Statistical analysis was carried out with the help of SPSS20.0 and SPSS Modeler18.1.Results:the most commonly used acupuncture points for postpartum depression are Baihui,Taichong,Sanyinjiao,Zusanli,Neiguan,Governor Meridian,foot Jueyin liver Meridian and foot Sun bladder Meridian,which are closely related to the treatment of postpartum depression.most doctors'clinical acupuncture treatment sites are head,limbs and back.The correlation analysis results obtained by SPSS Modeler software are Taichong-Neiguan-Zusanli,Taichong-Neiguan and Neiguan-Zusanli.Finally,the high-frequency acupoints are clustered and classified into four clusters,namely Taichong,Neiguan,Sanyinjiao and Zusanli.Hegu,Sishencong;Baihui,Shenmen;Pishu and Guanyuan.Conclusion:the rule of acupoint use of acupuncture and moxibustion in the treatment of postpartum depression through data mining can provide some reference for the clinical treatment of postpartum depression in the future.

Identification of core compositions of traditional Chinese medicine for Seborrheic Dermatitis using data mining techniques

Objective:To explore the clinical medication rule of seborrheic dermatitis in modern Chinese medicine by data mining,in order to benefit the clinical treatment of seborrheic dermatitis in traditional Chinese medicine.Methods:From January 1,2010 to September 4,2019,articles on Chinese medicine for seborrheic dermatitis were searched systematically in CNKI,VIP and Wan Fang databases.Prescription databases were established through the Chinese Medicine Inheritance assistant system to mine and analyze the rules of data.Results:69 researches were screened out,72 prescriptions for seborrheic dermatitis.13 drugs were used more than or equal to 15 times,and 9 pairs of commonly used drugs with correlation coefficient above 0.045 were selected.Six core combinations and two new prescriptions were obtained.Conclusion:Data mining method was used to analyze the high-frequency drugs and drug pairs,which reflected the treatment principle of clearing heat and removing dampness,nourishing blood and moistening dryness,promoting qi and strengthening spleen in the clinical treatment of seborrheic dermatitis,and provided more intuitive research evidence for the follow-up clinical treatment.

Research on Employment Data Mining for Higher Vocational Graduates

In order to make effective use a large amount of graduate data in colleges and universities that accumulate by teaching management of work, the paper study the data mining for higher vocational graduates database using the data mining technology. Using a variety of data preprocessing methods for the original data, and the paper put forward to mining algorithm based on commonly association rule Apriori algorithm, then according to the actual needs of the design and implementation of association rule mining system, has been beneficial to the employment guidance of college teaching management decision and graduates of the mining results.