Skip to main content
SpringerLink
Log in

RETRACTED ARTICLE: Building the electronic evidence analysis model based on association rule mining and FP-growth algorithm

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

This article was retracted on 30 November 2022

This article has been updated

Abstract

In China’s criminal procedure law, electronic data is a kind of independent evidence. With the development of big data technology, more and more attention has been paid to the examination and application of electronic evidence in criminal trials. In order to obtain hidden knowledge from confused electronic evidence, an electronic evidence analysis model based on data mining is proposed. The main research is to apply the association rule technology of data mining to the analysis of electronic evidence, analyze the shortcomings of the existing association rule mining algorithm, and put forward the improved algorithm of the existing algorithm and a new idea of the algorithm. Based on FP-growth algorithm, an improved algorithm (ISPO-tree algorithm) is put forward and the theoretical proof is given. This algorithm only needs to browse the database once and adds the function of supporting a small amount of modified evidence. This algorithm improves the time efficiency of data pre-processing by making similar rules to make unequal attribute values equal and can mine more association rules under the optimum conditions of support and redundancy, and it improves the effectiveness of electronic evidence and the accuracy of criminal trial.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig.. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Change history

References

  • Ab Rahman NH, Choo KKR (2015) A survey of information security incident handling in the cloud. Comput Secur 49:45–69

    Article  Google Scholar 

  • Amahalu NN, Beatrice E (2017) Determinants of audit quality: evidence from deposit money banks listed on nigeria stock exchange. Soc Sci Electron Publ 7(2):117–130

    Google Scholar 

  • Archontoulis SV, Miguez FE (2015) Nonlinear regression models and applications in agricultural research. Agron J 107(2):786–798

    Article  Google Scholar 

  • Blom C, Forbes DA, Foster C, Romanowsky AJ, Brodie JP (2018) The sluggs survey: new evidence for a tidal interaction between the early-type galaxies ngc 4365 and ngc 4342. Mon Not R Astron Soc 439(3):2420–2431

    Article  Google Scholar 

  • Bruhn M (2018) The impact of consulting services on small and medium enterprises: evidence from a randomized trial in Mexico 1, vol 102(2). Social Science Electronic Publishing, Amsterdam, pp 31–33(3)

    Google Scholar 

  • Caccianiga A, Antón S, Ballo L, Dallacasa D, Ceca RD, Fanali R et al (2018) Sdss j143244.91 + 301435.3: a link between radio-loud narrow-line seyfert 1 galaxies and compact steep-spectrum radio sources? Mon Not R Astron Soc 441(1):172–186

    Article  Google Scholar 

  • Canali C, Chiaraviglio L, Lancellotti R, Shojafar M (2018) Joint minimization of the energy costs from computing, data transmission, and migrations in cloud data centers. IEEE Trans Green Commun Netw 2(2):580–595

    Article  Google Scholar 

  • De La Torre-Díez I, López-Coronado M, Vaca C et al (2015) Cost-utility and cost-effectiveness studies of telemedicine, electronic, and mobile health systems in the literature: a systematic review. Telemed E Health 21(2):81–85

    Article  Google Scholar 

  • Dennehy D, Sammon D (2015) Trends in mobile payments research: a literature review. J Innov Manag 3(1):49–61

    Article  Google Scholar 

  • Drobinski P, Silva ND, Panthou G, Bastin S, Muller C, Ahrens B et al (2018) Scaling precipitation extremes with temperature in the mediterranean: past climate assessment and projection in anthropogenic scenarios. Clim Dyn 51(3):1237–1257

    Article  Google Scholar 

  • Fang B, Ye Q, Kucukusta D et al (2016) Analysis of the perceived value of online tourism reviews: influence of readability and reviewer characteristics. Tour Manag 52:498–506

    Article  Google Scholar 

  • Feld J, Zölitz U (2017) Understanding peer effects: on the nature, estimation and channels of peer effects. Soc Sci Electron Publ 35(2):387–428

    Google Scholar 

  • Green RC, Goddard KAB, Jarvik GP et al (2016) Clinical sequencing exploratory research consortium: accelerating evidence-based practice of genomic medicine. Am J Hum Genet 98(6):1051–1066

    Article  Google Scholar 

  • Grosvold J, Hoejmose S, Roehrich J (2017) Squaring the circle: management, measurement and performance of sustainability in supply chains. Soc Sci Electron Publ 19(3):292–305

    Google Scholar 

  • Jirak M (2017) Uniform change point tests in high dimension. Ann Stat 43(6):2451–2483

    MathSciNet  MATH  Google Scholar 

  • Kumar D, Bezdek JC, Palaniswami M, Rajasegarar S, Leckie C, Havens TC (2017a) A hybrid approach to clustering in big data. IEEE Trans Cybern 46(10):2372–2385

    Article  Google Scholar 

  • Kumar D, Bezdek JC, Rajasegarar S, Leckie C, Palaniswami M (2017b) A visual-numeric approach to clustering and anomaly detection for trajectory data. Vis Comput Int J Comput Graph 33(3):265–281

    Google Scholar 

  • Law R, Buhalis D, Cobanoglu C (2014a) Progress on information and communication technologies in hospitality and tourism. Int J Contemp Hosp Manag 26(5):727–750

    Article  Google Scholar 

  • Law CW, Chen Y, Shi W et al (2014b) voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol 15(2):R29

    Article  Google Scholar 

  • Liñán F, Fayolle A (2015) A systematic literature review on entrepreneurial intentions: citation, thematic analyses, and research agenda. Int Entrep Manag J 11(4):907–933

    Article  Google Scholar 

  • Pichan A, Lazarescu M, Soh ST (2015) Cloud forensics: technical challenges, solutions and comparative analysis. Digit Investig 13:38–57

    Article  Google Scholar 

  • Quick D, Choo KKR (2014) Impacts of increasing volume of digital forensic data: a survey and future research challenges. Digit Investig 11(4):273–294

    Article  Google Scholar 

  • Quick D, Choo KKR (2016) Big forensic data reduction: digital forensic images and electronic evidence. Cluster Comput 19(2):723–740

    Article  Google Scholar 

  • Sallis JF, Owen N, Fisher E (2015) Ecological models of health behavior. Health Behav Theory Res Pract 5:43–64

    Google Scholar 

  • Schmidt FP, Schmitt C, Hochadel M, Giannitsis E, Darius H, Maier LS et al (2018) Invasive treatment of nstemi patients in german chest pain units—evidence for a treatment paradox. Int J Cardiol 255:15–19

    Article  Google Scholar 

  • Smith MJ, Plotkin SR (2018) Neurofibromatosis and schwannomatosis. Semin Neurol 38(01):073–085

    Article  Google Scholar 

  • Tzanis G (2017) Biological and medical big data mining. Int J Knowl Discov Bioinform 4(1):42–56

    Article  Google Scholar 

  • Vilaça R, Rui O, Pereira J (2017) A correlation-aware data placement strategy for key-value stores. Lect Notes Comput Sci 6723(1):214–227

    Google Scholar 

  • Xu L, Jiang C, Wang J, Yuan J, Ren Y (2017) Information security in big data: privacy and data mining. IEEE Access 2(2):1149–1176

    Google Scholar 

Download references

Acknowledgements

This work was supported by “Probation application evaluation mechanism empirical research” of Ministry of education humanities and social science research youth fund (Project No. 18YJC820067).

Author information

Authors and Affiliations

  1. Police Department, Anhui Vocational College of Police Officers, Hefei, China

    Yilan Wu

  2. Law School, Anhui University, Hefei, China

    Jing Zhang

Authors
  1. Yilan Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yilan Wu.

Ethics declarations

Conflict of interest

All Authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

It was obtained from all individual participants included in the study.

Additional information

Communicated by Mu-Yen Chen.

Communicated by Mu-Yen Chen.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, Y., Zhang, J. RETRACTED ARTICLE: Building the electronic evidence analysis model based on association rule mining and FP-growth algorithm. Soft Comput 24, 7925–7936 (2020). https://doi.org/10.1007/s00500-019-04032-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-019-04032-0

Keywords

Search

Navigation