Terms mining in document-based NoSQL: Response to unstructured data

Richard K. Lomotey, Ralph Deters

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Unstructured data mining has become topical recently due to the availability of high-dimensional and voluminous digital content (known as 'Big Data') across the enterprise spectrum. The Relational Database Management Systems (RDBMS) have been employed over the past decades for content storage and management, but, the ever-growing heterogeneity in today's data calls for a new storage approach. Thus, the NoSQL database has emerged as the preferred storage facility nowadays since the facility supports unstructured data storage. This creates the need to explore efficient data mining techniques from such NoSQL systems since the available tools and frameworks which are designed for RDBMS are often not directly applicable. In this paper, we focused on topics and terms mining, based on clustering, in document-based NoSQL. This is achieved by adapting the architectural design of an analytics-as-a-service framework and the proposal of the Viterbi algorithm to enhance the accuracy of the terms classification in the system. The results from the pilot testing of our work show higher accuracy in comparison to some previously proposed techniques such as the parallel search.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014
EditorsPeter Chen, Peter Chen, Hemant Jain
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages661-668
Number of pages8
ISBN (Electronic)9781479950577
DOIs
StatePublished - Sep 22 2014
Event3rd IEEE International Congress on Big Data, BigData Congress 2014 - Anchorage, United States
Duration: Jun 27 2014Jul 2 2014

Publication series

NameProceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014

Other

Other3rd IEEE International Congress on Big Data, BigData Congress 2014
CountryUnited States
CityAnchorage
Period6/27/147/2/14

All Science Journal Classification (ASJC) codes

  • Computer Science Applications

Fingerprint Dive into the research topics of 'Terms mining in document-based NoSQL: Response to unstructured data'. Together they form a unique fingerprint.

Cite this