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Titlebook: Intelligent Information and Database Systems; 5th Asian Conference Ali Selamat,Ngoc Thanh Nguyen,Habibollah Haron Conference proceedings 20

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發(fā)表于 2025-3-30 08:40:02 | 只看該作者
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發(fā)表于 2025-3-30 20:26:04 | 只看該作者
Hybrid-Learning Based Data Gathering in Wireless Sensor Networksart of prediction based data gathering. A majority of the existing prediction based data gathering approaches consider centralized and some others use localized and distributed learning and model updates. Our conjecture in this work is that no single learning approach may not be optimal for all the
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發(fā)表于 2025-3-30 21:56:33 | 只看該作者
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發(fā)表于 2025-3-31 02:34:48 | 只看該作者
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發(fā)表于 2025-3-31 08:57:36 | 只看該作者
A Semantically Enhanced Tag-Based Music Recommendation Using Emotion Ontology based on tag frequency, our approach is based on semantics of tags. In order to extract semantics of tags, we developed the emotion ontology for music called UniEmotion, which categorizes tags into positive emotional tags, negative emotional tags, and factual tags. According to the types of the tag
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發(fā)表于 2025-3-31 09:18:07 | 只看該作者
A Method for Determination of an Opening Learning Scenario in Intelligent Tutoring Systemsorter time. Our previous research pointed out that the personalization of the learning scenario allows to satisfy the mentioned postulates. In this paper the method for determination of an opening learning scenario is presented. Before a student begins to learn an?opening scenario is determined base
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發(fā)表于 2025-3-31 16:52:47 | 只看該作者
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發(fā)表于 2025-3-31 17:59:54 | 只看該作者
Using Subtree Agreement for Complex Tree Integration Tasksplex tree to model other common hierarchical structures. Complex tree integration is parametrized by specific integration criteria. Sub-tree agreement is a group of criteria that describes the relation of sub-tree number and structure between input trees and the integrated tree. This paper provides
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發(fā)表于 2025-4-1 01:41:44 | 只看該作者
Data Sets for Offline Evaluation of Scholar’s Recommender Systemtical analysis. However, many data sets are domain and application dependent and cannot be engaged in different domains. This paper presents the construction of data sets for the offline evaluation of a scholar’s recommender system that suggests papers to scholars based on their background knowledge
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