Combining Bottom-up and Top-down Generation of Interactive Knowledge Maps for Enterprise Search

Kaufmann, Michael; Wilke, Gwendolin; Portmann, Edy; Hinkelmann, Knut (October 2014). Combining Bottom-up and Top-down Generation of Interactive Knowledge Maps for Enterprise Search. In: Buchmann, Robert; Kifor, Claudiu Vasile; Yu, Jian (eds.) Knowledge Science, Engineering and Management. 7th International Conference on Knowledge Science, Engineering and Management: KSEM 2014. Lecture Notes in Artificial Intelligence LNAI: Vol. 8793 (pp. 186-197). Springer 10.1007/978-3-319-12096-6_17

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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 ana- lytics engine extracts knowledge structures from data inductively, and the en- terprise 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 rec- ords. 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.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems
03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems > Information Management

UniBE Contributor:

Portmann, Edy

Subjects:

000 Computer science, knowledge & systems
300 Social sciences, sociology & anthropology
600 Technology > 650 Management & public relations

ISBN:

978-3-319-12095-9

Series:

Lecture Notes in Artificial Intelligence LNAI

Publisher:

Springer

Projects:

[388] Knowledge Aggregation, Representation and Reasoning

Language:

English

Submitter:

Sara D'Onofrio

Date Deposited:

13 Oct 2014 14:11

Last Modified:

02 Nov 2015 09:01

Publisher DOI:

10.1007/978-3-319-12096-6_17

BORIS DOI:

10.7892/boris.58958

URI:

https://boris.unibe.ch/id/eprint/58958

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