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Titlebook: Intelligent Information and Database Systems; 8th Asian Conference Ngoc Thanh Nguyen,Bogdan Trawiński,Tzung-Pei Hong Conference proceedings

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樓主: 果園
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發(fā)表于 2025-3-25 03:54:31 | 只看該作者
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發(fā)表于 2025-3-25 09:04:58 | 只看該作者
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發(fā)表于 2025-3-25 15:37:15 | 只看該作者
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發(fā)表于 2025-3-25 17:13:22 | 只看該作者
Knowledge Base Refinement with Gamified Crowdsourcingajor application domain of human computation. Using the concept of crowdsourcing, refinement tasks can be delegated to many casual users over a network. In addition, gamification such as games with a purpose (GWAP) is a useful idea to motivate workers in crowdsourcing by making a task into a playful
25#
發(fā)表于 2025-3-25 23:25:38 | 只看該作者
Argumentation Framework for Merging Stratified Belief Bases game in which participating agents use argumentation technique to debate on their own belief bases to achieve consensus i.e. a common belief base. To this end, we introduce a framework for merging belief by argumentation in which an argumentation-based belief merging protocol is proposed and a set
26#
發(fā)表于 2025-3-26 03:53:12 | 只看該作者
An Ontology-Based Knowledge Representation of MCDA Methodswhich takes into consideration the most essential characteristics. This taxonomy, in the conceptualization process, was written by means of description logic and then it was implemented in the OWL language in the form of ontology representing field knowledge in the scope of MCDA methods. The researc
27#
發(fā)表于 2025-3-26 06:40:32 | 只看該作者
28#
發(fā)表于 2025-3-26 10:06:59 | 只看該作者
Temporal Ontology Representation and Reasoning Using Ordinals and Sets for Historical Eventsuery generation processes. This paper proposes a temporal representation model that can support qualitative and quantitative temporal information on historical ontology by applying the concept of ordinals and sets and introduces operators that allow a QA system to easily handle complex temporal quer
29#
發(fā)表于 2025-3-26 16:22:21 | 只看該作者
Measuring Propagation Phenomena in Social Networks: Promising Directions and Open Issuested data also increased several times. To understand and predict the spread of information over a time period in online social networks researchers attempt to quantitatively model and measure the whole process. A number of different statistics aimed at measuring the spread were suggested. Many resea
30#
發(fā)表于 2025-3-26 19:25:53 | 只看該作者
Visualizing Learning Activities in Social Networkt cohorts in the age of massification of education market, this approach has become attractive. Recent advances in learning analytics and data visualization further proved to be useful in encouraging collaborative learning. On the other hand, information of social networks can be too complex to visu
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