Intelligent information processing for building university knowledge base

There are many ready-to-use software solutions for building institutional scientific information platforms, most of which have functionality well suited to repository needs. However, there have already been discussions about various problems with institutional digital libraries. As a remedy, an appr...

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Bibliographic Details
Published in:Journal of intelligent information systems 2017-02, Vol.48 (1), p.141-163
Main Authors: Koperwas, Jakub, Skonieczny, Łukasz, Kozłowski, Marek, Andruszkiewicz, Piotr, Rybiński, Henryk, Struk, Wacław
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Buildings
Computer Science
Data acquisition
Data mining
Data Structures and Information Theory
Digital libraries
Enrichment
Information processing
Information Storage and Retrieval
Institutional repositories
Intelligent systems
IT in Business
Knowledge
Knowledge base
Natural Language Processing (NLP)
Platforms
Remedies
Research data management
Semantic web
Semantics
Software
Studies
Universities
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Summary:There are many ready-to-use software solutions for building institutional scientific information platforms, most of which have functionality well suited to repository needs. However, there have already been discussions about various problems with institutional digital libraries. As a remedy, an approach that is researcher-centric (rather than document-centric) has been proposed recently in some systems. This paper is devoted to research aimed at tools for building knowledge bases for university research. We focus on the AI methods that have been elaborated and applied practically within our platform for building such knowledge bases. In particular we present a novel approach to data acquisition and the semantic enrichment of the acquired data. In addition, we present the algorithms applied in the real life system for experts profiling and retrieval.
ISSN:0925-9902
1573-7675
DOI:10.1007/s10844-015-0393-0