Applying ASP for Knowledge-Based Link Prediction With Explanation Generation in Feature-Rich NetworksDownload PDFOpen Website

Published: 01 Jan 2021, Last Modified: 10 Nov 2023IEEE Trans. Netw. Sci. Eng. 2021Readers: Everyone
Abstract: Link prediction is challenging, especially based on (scarce) historic data or in cold start scenarios. In this paper, we show how to apply answer set programming (ASP) for formalizing link prediction in feature-rich networks, that is - in particular - using domain knowledge for network (and graph) analysis. We show, that applying ASP for link prediction provides a powerful declarative approach, as exemplified using simple predictors, and demonstrate according explanation generation using ASP. We present the application of the proposed methodological approach for explicative link prediction and analysis with explanation generation using different datasets.
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