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Text Causal Discovery Based on Sequence Structure Information
Causality forms the basis for reasoning and decision-making in artificial intelligence systems. To take advantage of the vast amount of textual data...
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Graph contrastive learning with cross-encoder for community discovery
Community detection is a crucial task that enables the extraction of valuable knowledge and patterns from complex networks. However, the node labels...
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Discovery, Retrieval
This chapter describes the emergence of the differentiation between traditional librarianship with its focus on collections, which has become...
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Discovery of Workflow Patterns - A Comparison of Process Discovery Algorithms
Process mining provides a set of techniques and algorithms to analyze, support, and improve business processes based on process execution data....
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Discovery of contextual factors using clustering
The Knowledge Discovery and Data Mining (KDDM) is a growing field of study argued to be very useful in discovering knowledge hidden in large...
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Mobile Devices as Information Discovery Tools for Young Children
With the increased use of mobile devices by young children, the question arises whether these devices also serve as tools for information discovery...
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Parallel Flexible Heuristic Miner for Process Discovery
Process discovery aims to construct a business process model by extracting valuable information from event logs. To extract process models from event...
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Semantically realizing discovery and composition for RESTful web services
The processes of service discovery and composition are crucial tasks in application development driven by Web Services. However, with RESTful Web...
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Efficient Hierarchical Reinforcement Learning via Mutual Information Constrained Subgoal Discovery
Goal-conditioned hierarchical reinforcement learning has demonstrated impressive capabilities in addressing complex and long-horizon tasks. However,...
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Power analysis for causal discovery
Causal discovery algorithms have the potential to impact many fields of science. However, substantial foundational work on the statistical properties...
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River runoff causal discovery with deep reinforcement learning
AbstractCausal discovery from river runoff data aids flood prevention and mitigation strategies, garnering attention in climate and earth science....
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Analyzing Healthcare Processes with Incremental Process Discovery: Practical Insights from a Real-World Application
AbstractMost process mining techniques are primarily automated, meaning that process analysts input information and receive output. As a result,...
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Music information visualization and classical composers discovery: an application of network graphs, multidimensional scaling, and support vector machines
This article illustrates different information visualization techniques applied to a database of classical composers and visualizes both the...
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A framework for REST services discovery and composition
The increasing number of Restful web services/Rest APIs and their adoption by leading Internet companies grabbed the attention of the industry as...
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Knowledge Discovery as Translation
This paper discusses a view to capture discovery as a translation from non-symbolic to symbolic representation. First, a relation between symbolic...
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Enhancing knowledge discovery and management through intelligent computing methods: a decisive investigation
Knowledge Discovery and Management (KDM) encompasses a comprehensive process and approach involving the creation, discovery, capture, organization,...
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A credible traffic prediction method based on self-supervised causal discovery
Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence (AI)...
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Distributional constraint discovery for intelligent auditing
Constraint discovery in relational databases aims to find constraints that express dependency relationships among a set of attributes and has...
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Generalizing truth discovery by incorporating multi-truth features
Truth discovery is the fundamental technique for resolving the conflicts between the information provided by different data sources by detecting the...
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Imposing Rules in Process Discovery: An Inductive Mining Approach
Process discovery aims to discover descriptive process models from event logs. These discovered process models depict the actual execution of a...