Data mining from NoSQL document-append style storages

Richard K. Lomotey, Ralph Deters

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

3 Scopus citations


The modern data economy, which has been described as "Big Data", has changed the status quo on digital content creation and storage. While data storage has followed the schema-dictated approach for decades, the recent nature of digital content, which is widely unstructured, creates the need to adopt different storage techniques. Thus, the NoSQL database systems have been proposed to accommodate most of the content being generated today. One of such NoSQL databases that have received significant enterprise adoption is the document-append style storage. The emerging concern and challenge however is that, research and tools that can aid data mining processes from such NoSQL databases is generally lacking. Even though document-append style storages allow data accessibility as Web services and over URL/I, building a corresponding data mining tool deviates from the underlying techniques governing web crawlers. Also, existing data mining tools that have been designed for schema-based storages (e.g., RDBMS) are misfits. Hence, our goal in this work is to design a unique data analytics tool that enables knowledge discovery through information retrieval from document-append style storage. The tool is algorithmically built on the inference-based Apriori, which aids us to achieve optimization of the search duration. Preliminary test results of the proposed tool also show high accuracy in comparison to other approaches that were previously proposed.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Conference on Web Services, ICWS 2014
EditorsDavid De Roure, Bhavani Thuraisingham, Jia Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781479950546
StatePublished - 2014
Event2014 21st IEEE International Conference on Web Services, ICWS 2014 - Anchorage, United States
Duration: Jun 27 2014Jul 2 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Web Services, ICWS 2014


Other2014 21st IEEE International Conference on Web Services, ICWS 2014
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Software


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