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Titlebook: Knowledge Discovery, Knowledge Engineering and Knowledge Management; 7th International Jo Ana Fred,Jan L.G. Dietz,Joaquim Filipe Conference

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31#
發(fā)表于 2025-3-26 23:36:35 | 只看該作者
32#
發(fā)表于 2025-3-27 02:45:09 | 只看該作者
Model-Intersection Problems and Their Solution Schema Based on Equivalent Transformation-order logic and query-answering (QA) problems in pure Prolog and deductive databases. We propose a general schema for solving MI problems by equivalent transformation (ET), where problems are solved by repeated simplification. The correctness of this solution schema is shown. This general schema is
33#
發(fā)表于 2025-3-27 08:37:33 | 只看該作者
Representing and Managing Unbalanced Multi-setse imperfection. Several approaches have dealt with this kind of data. The most known are fuzzy logic and multi-valued logic. These latter propose a linguistic modeling using linguistic terms that are uniformly distributed on a scale. However, in some cases, we need to assess qualitative aspects by m
34#
發(fā)表于 2025-3-27 09:27:58 | 只看該作者
Ranking with Ties of OWL Ontology Reasoners Based on Learned Performances languages such as OWL 2 DL. Nevertheless, it is well-accepted that there is no outstanding reasoner that can outperform in all input ontologies. Thus, deciding the most suitable reasoner for an ontology based application is still a time and effort consuming task. In this paper, we suggest to develo
35#
發(fā)表于 2025-3-27 14:45:07 | 只看該作者
36#
發(fā)表于 2025-3-27 19:41:55 | 只看該作者
Employing Knowledge Artifacts to Develop Time-Depending Expert Systemsearch trend. The Expert Systems’ technology should be able to face this interesting challenge, promoting the development of innovative frameworks runnable on wearables and mobile operating systems. In particular, users and domain experts could be able to interact directly, minimizing the role of kno
37#
發(fā)表于 2025-3-27 23:29:53 | 只看該作者
Knowledge Discovery, Knowledge Engineering and Knowledge Management7th International Jo
38#
發(fā)表于 2025-3-28 05:44:36 | 只看該作者
39#
發(fā)表于 2025-3-28 06:45:09 | 只看該作者
Is Bitcoin’s Market Predictable? Analysis of Web Search and Social Mediased in large-scale collections of daily Twitter posts, can be used to predict the Bitcoin market too. We achieved significant cross correlation outcomes, demonstrating the search and social volumes power to anticipate trading volumes of Bitcoin currency.
40#
發(fā)表于 2025-3-28 11:55:28 | 只看該作者
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