Accession Number : ADA591734


Title :   Lexical Link Analysis Application: Improving Web Service to Acquisition Visibility Portal


Descriptive Note : Research rept.


Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA GRADUATE SCHOOL OF OPERATIONAL AND INFORMATION SCIENCES


Personal Author(s) : Zhao, Ying ; Gallup, Shelley P ; MacKinnon, Douglas J


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a591734.pdf


Report Date : 30 Sep 2013


Pagination or Media Count : 44


Abstract : Lexical Link Analysis (LLA) is a form of text mining in which word meanings are represented in lexical terms (e.g., word pairs) of a word network. In the past, we have shown how LLA can systematically and automatically discover new patterns in large-scale defense acquisition data on multiple programs as indicators for program or investment performances. We also started to apply LLA to understand the quality of the data by comparing categories of information and detecting data gaps. Last year, we examined the Acquisition Visibility Portal (AVP), which is a critical tool that provides the DoD-wide acquisition community with authoritative and accurate data services. We reported the first program from AVP to have undergone a relatively comprehensive LLA analysis. This year, we found that there is much consensus or consistency in the various categories (e.g., acquisition and engineering communities) of artifacts, yet gaps or low correlations seem to characterize the majority of the data for the relations among these categories. LLA, however, is able to discover in detail where the gaps and inconsistencies in the data reside. The findings offered in this report can help decision-makers improve their resource and big data management to better understand how particular acquisition strategies may affect the desired return on investment (ROI) among projects.


Descriptors :   *AUTOMATION , *DATA MINING , *DOCUMENTS , *INTERNET , *LINKAGES , *MILITARY PROCUREMENT , *SEMANTICS , ACCURACY , ARTIFACTS , CONSISTENCY , CORRELATION , DATA MANAGEMENT , DEPARTMENT OF DEFENSE , INFORMATION RETRIEVAL , LEARNING MACHINES , QUALITY , WORDS(LANGUAGE)


Subject Categories : Information Science
      Linguistics
      Cybernetics
      Logistics, Military Facilities and Supplies


Distribution Statement : APPROVED FOR PUBLIC RELEASE