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On Detecting and Removing Superficial Redundancy in Vector Databases

Author

Listed:
  • Noemí DeCastro-García
  • Ángel Luis Muñoz Castañeda
  • Mario Fernández Rodríguez
  • Miguel V. Carriegos

Abstract

A mathematical model is proposed in order to obtain an automatized tool to remove any unnecessary data, to compute the level of the redundancy, and to recover the original and filtered database, at any time of the process, in a vector database. This type of database can be modeled as an oriented directed graph. Thus, the database is characterized by an adjacency matrix. Therefore, a record is no longer a row but a matrix. Then, the problem of cleaning redundancies is addressed from a theoretical point of view. Superficial redundancy is measured and filtered by using the 1-norm of a matrix. Algorithms are presented by Python and MapReduce, and a case study of a real cybersecurity database is performed.

Suggested Citation

  • Noemí DeCastro-García & Ángel Luis Muñoz Castañeda & Mario Fernández Rodríguez & Miguel V. Carriegos, 2018. "On Detecting and Removing Superficial Redundancy in Vector Databases," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-14, May.
    • Handle: RePEc:hin:jnlmpe:3702808
    DOI: 10.1155/2018/3702808
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