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Combining Bottom-Up and Top-Down Generation of Interactive Knowledge Maps for Enterprise Search

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 8793)

Abstract

Our research project develops an intranet search engine with concept-browsing functionality, where the user is able to navigate the conceptual level in an interactive, automatically generated knowledge map. This knowledge map visualizes tacit, implicit knowledge, extracted from the intranet, as a network of semantic concepts. Inductive and deductive methods are combined; a text analytics engine extracts knowledge structures from data inductively, and the enterprise ontology provides a backbone structure to the process deductively. In addition to performing conventional keyword search, the user can browse the semantic network of concepts and associations to find documents and data records. Also, the user can expand and edit the knowledge network directly. As a vision, we propose a knowledge-management system that provides concept-browsing, based on a knowledge warehouse layer on top of a heterogeneous knowledge base with various systems interfaces. Such a concept browser will empower knowledge workers to interact with knowledge structures.

Keywords

  • knowledge technology
  • knowledge engineering
  • concept extraction
  • enterprise ontology
  • enterprise search
  • concept browsing

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Kaufmann, M., Wilke, G., Portmann, E., Hinkelmann, K. (2014). Combining Bottom-Up and Top-Down Generation of Interactive Knowledge Maps for Enterprise Search. In: Buchmann, R., Kifor, C.V., Yu, J. (eds) Knowledge Science, Engineering and Management. KSEM 2014. Lecture Notes in Computer Science(), vol 8793. Springer, Cham. https://doi.org/10.1007/978-3-319-12096-6_17

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  • DOI: https://doi.org/10.1007/978-3-319-12096-6_17

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12095-9

  • Online ISBN: 978-3-319-12096-6

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