Lexical Link Analysis (LLA) Application: Improving Web Service to Defense Acquisition Visibility Environment

Abstract

We have been studying DoD acquisition decision making since 2009. The US DoD acquisition process is extremely complex. There are three key processes that must work in concert to deliver capabilities: determining warfighters requirements and needs; planning the DoD budget, and procuring final products. Each process produces large amounts of information (Big Data). There is a critical need for automation, validation, and discovery to help acquisition professionals, decision makers and researchers understand the important content within large data sets and optimize DoD resources throughout the processes. Lexical Link Analysis (LLA) can help by applying automation to reveal and depictto decision-makersthe correlations, associations, and program gaps across all, or subsets of, acquisition programs examined over many years. This enables strategic understanding of data gaps and potential trends, and can inform managers where areas might be exposed to higher program risk, and how resource and big data management might affect the desired return on investment (ROI) among projects. In this report, we describe new developments in analytics and visualization, how LLA is adaptive to Big Data Architecture and Analytics (BDAA), and reveal needs for Big Acquisition Data used in Defense Acquisition Visibility Environment (DAVE).

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2015
Accession Number
AD1014634

Entities

People

  • Douglas J. MacKinnon
  • Shelley P. Gallup
  • Ying Zhao

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Anomaly Detection
  • Big Data
  • Change Detection
  • Data Fusion
  • Data Management
  • Data Mining
  • Data Science
  • Deep Learning
  • Information Science
  • Knowledge Management
  • Machine Learning
  • Network Science
  • Pattern Recognition
  • Public Policy
  • Test And Evaluation
  • Unsupervised Machine Learning

Readers

  • Defense Acquisition Program Management
  • Distributed Systems and Data Platform Development