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Knowledge-based Sequence Mining with ASP
Martin Gebser, Thomas Guyet, René Quiniou, Javier Romero, Torsten Schaub

Knowledge-based Sequence Mining with ASP

Science & Mathematics Published 2016 Verification Pending

Overview & Synopsis

We introduce a framework for knowledge-based sequence mining, based on Answer Set Programming (ASP). We begin by modeling the basic task and refine it in the sequel in several ways. First, we show how easily condensed patterns can be extracted by modular extensions of the basic approach. Second, we illustrate how ASP's preference handling capacities can be exploited for mining patterns of interest. In doing so, we demonstrate the ease of incorporating knowledge into the ASP-based mining process. To assess the trade-off in effectiveness, we provide an empirical study comparing our approach with a related sequence mining mechanism.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Knowledge-based Sequence Mining with ASP
Author / Organization Martin Gebser, Thomas Guyet, René Quiniou, Javier Romero, Torsten Schaub
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2016
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-65097
Original Source Link Visit Source Page on hal.science »