Knowledge-based extraction of intellectual capital-related information from unstructured data

Yue Hong Eric Tsui, W. M. Wang, Linlin Cai, Chi Fai Cheung, Wing Bun Lee

Research output: Journal article publicationJournal articleAcademic researchpeer-review

30 Citations (Scopus)

Abstract

Nowadays, there is an increasing demand for the identification of an organization's intellectual capital (IC) for decision support and providing important managerial insights in knowledge-intensive industries. In traditional approaches, identification of an organization's IC is usually done manually through interviews, surveys, workshops, etc. These methods are labor and time intensive and the quality of the results is highly dependent on, among other things, the experience of the investigators. This paper presents a Knowledge-based Intellectual Capital Extraction (KBICE) algorithm which incorporates the technologies of computational linguistics and artificial intelligence (AI) for automatic processing of unstructured data and extraction of important IC-related information. The performance of KBICE was assessed through a series of experiments conducted by using publicly available financial reports from the banking industry as the testing batch and encouraging results have been obtained. The results showed that, through the use of hybrid intelligent matching strategies, it is possible to extract commonly referred IC-related information from unstructured data automatically. IC information analyst can rely on this method as an additional mean to identify and extract the commonly sought IC information from financial reports in a fast, systematic and reliable manner.
Original languageEnglish
Pages (from-to)1315-1325
Number of pages11
JournalExpert Systems with Applications
Volume41
Issue number4 PART 1
DOIs
Publication statusPublished - 1 Jan 2014

Keywords

  • Case-based reasoning
  • Information extraction
  • Intellectual capital management
  • Knowledge-based systems
  • Unstructured information management

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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