Analytics-as-a-service (AaaS) tool for unstructured data mining: Towards knowledge discovery in big data

Richard K. Lomotey, Ralph Deters

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

8 Scopus citations

Abstract

Analytics-as-a-Service (AaaS) has become indispensable because it affords stakeholders to discover knowledge in Big Data. Previously, data stored in data warehouses follow some schema and standardization which leads to efficient data mining. However, the "Big Data" epoch has witnessed the rise of structured, semi-structured, and unstructured data, a trend that motivated enterprises to employ the NoSQL data storages to accommodate the high-dimensional data. In this paper, we introduce an AaaS tool that aims at accomplishing terms and topics extraction and organization from unstructured data sources such as NoSQL databases and textual contents (e.g., websites). The primary accomplishment in this paper is the detail justification of the architectural design of our proposed framework. This includes the proposed algorithms (e.g., concurrency search, linear search, etc.) and the performance of macro tasks such as filtering, tagging, and so on.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Conference on Cloud Engineering, IC2E 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages319-324
Number of pages6
ISBN (Electronic)9781479937660
DOIs
StatePublished - Sep 18 2014
Event2nd IEEE International Conference on Cloud Engineering, IC2E 2014 - Boston, United States
Duration: Mar 10 2014Mar 14 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Cloud Engineering, IC2E 2014

Other

Other2nd IEEE International Conference on Cloud Engineering, IC2E 2014
CountryUnited States
CityBoston
Period3/10/143/14/14

All Science Journal Classification (ASJC) codes

  • Software

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