Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Enabling technology for knowledge sharing
AI Magazine
Journal of the American Society for Information Science - Special issue on science and technology indicators
Software engineering as seen through its research literature: a study in co-word analysis
Journal of the American Society for Information Science
A vector space model for automatic indexing
Communications of the ACM
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
Constructing intelligent and open mobile commerce using a semantic web approach
Journal of Information Science
Using ontology network analysis for research document recommendation
Expert Systems with Applications: An International Journal
An ontology and peer-to-peer based data and service unified discovery system
Expert Systems with Applications: An International Journal
Bibliometric maps of field of science
Information Processing and Management: an International Journal - Special issue: Infometrics
UFOme: An ontology mapping system with strategy prediction capabilities
Data & Knowledge Engineering
Hi-index | 0.00 |
This study proposes an empirical way for determining probability of network tie formation between network actors. In social network analysis, it is a usual problem that information for determining whether or not a network tie should be formed is missing for some network actors, and thus network can only be partially constructed due to unavailability of information. This methodology proposed in this study is based on network actors' similarities calculations by Vector-Space Model to calculate how possible network ties can be formed. Also, a threshold value of similarity for deciding whether or not a network tie should be generated is suggested in this study. Four ontology-based knowledge networks, with journal paper or research project as network actors, constructed previously are selected as the targets of this empirical study: (1) Technology Foresight Paper Network: 181 papers and 547 keywords, (2) Regional Innovation System Paper Network: 431 papers and 1165 keywords, (3) Global Sci-Tech Policy Paper Network: 548 papers and 1705 keywords, (4) Taiwan's Sci-Tech Policy Project Network: 143 research projects and 213 keywords. The four empirical investigations allow a cut-off threshold value calculated by Vector-Space Model to be suggested for deciding the formation of network ties when network linkage information is unavailable.