Text based knowledge discovery with information flow analysis

Song, Dawei and Bruza, Peter (2006). Text based knowledge discovery with information flow analysis. In: ed. Frontiers of WWW Research and Development - APWeb 2006. Lecture Notes in Computer Science, Volume 384. Springer: Berlin, pp. 692–701.

DOI: https://doi.org/10.1007/11610113_60

Abstract

Information explosion has led to diminishing awareness: disciplines are becoming increasingly specialized; individuals and groups are becoming ever more insular. This paper considers how awareness can be enhanced via text-based knowledge discovery. Knowledge representation is motivated from a socio-cognitive perspective. Concepts are represented as vectors in a high dimensional semantic space automatically derived from a text corpus. Information flow computation between vectors is proposed as a means of discovering implicit associations between concepts. The potential of information flow analysis in text based knowledge discovery has been demonstrated by two case studies: literature-based scientific discovery by attempting to simulate Swanson’s Raynaud-fish oil discovery in medical texts; and automatic category derivation from document titles. There is some justification to believe that the techniques create awareness of new knowledge.

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