Please use this identifier to cite or link to this item:
https://dair.nps.edu/handle/123456789/2476
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ying Zhao | |
dc.contributor.author | Shelley Gallup | |
dc.contributor.author | Douglas J. MacKinnon | |
dc.date.accessioned | 2020-03-16T18:17:55Z | - |
dc.date.available | 2020-03-16T18:17:55Z | - |
dc.date.issued | 2010-10-28 | |
dc.identifier.citation | Published--Unlimited Distribution | |
dc.identifier.uri | https://dair.nps.edu/handle/123456789/2476 | - |
dc.description | Acquisition Management / NPS Faculty Research | |
dc.description.abstract | DoD acquisition is an extremely complex system, comprised of myriad stakeholders, processes, people, activities, and organizational structures. We believe that the application of a data-driven automation system namely, Lexical Link Analysis (LLA) can facilitate acquisition researchers data sense-making dilemma and help reveal important connections (concepts) and patterns derived from dynamic, voluminous, and on-going data collection. In this past year, we have demonstrated the LLA method to discover valid associations among disparate, unstructured data sets that would have otherwise required lengthy and expensive man-hours to achieve. We analyzed how Trident Warrior 10 technology capabilities link to classified Navy Urgent Need Statements (UNSs). We validated lexical links against the links identified by human experts in the context of realistic, large-scale data sets. We demonstrated using the LLA methods to discover statistically significant correlations. We discovered that the current congressional budget justification practice for Research, Development, Test and Evaluation (RDT&E) tends to allocate resources to avoid overlapping efforts and to fund new and unique projects. We also discovered that the Program Elements (PEs) that match the warfighters requirements obtain more overall attention and less budget reduction compared to the ones without matches. This effort will result in assisting acquisition professionals in improving their decision-making among competing programs and in selecting those that satisfy Navy objectives, thus achieving the Navys goal of improved operational capability. | |
dc.description.sponsorship | Acquisition Research Program | |
dc.language | English (United States) | |
dc.publisher | Acquisition Research Program | |
dc.relation.ispartofseries | Data Analysis | |
dc.relation.ispartofseries | NPS-AM-10-174 | |
dc.subject | Lexical Link Analysis | |
dc.subject | Text Mining | |
dc.subject | Data Mining | |
dc.subject | Program Elements | |
dc.subject | Major DoD Acquisition Programs | |
dc.subject | Universal Joint Task Lists | |
dc.subject | Resource Allocation | |
dc.subject | Warfighter Requirement | |
dc.subject | Urgent Need Statements | |
dc.subject | Unstructured Data | |
dc.subject | Data-Driven Automation | |
dc.title | Towards Real-Time Program Awareness via Lexical Link Analysis | |
dc.type | Technical Report | |
Appears in Collections: | Sponsored Acquisition Research & Technical Reports |
Files in This Item:
File | Size | Format | |
---|---|---|---|
NPS-AM-10-174.pdf | 5.7 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.