ArticleEntropy (Basel, Switzerland)2018
Recognizing Information Feature Variation: Message Importance Transfer Measure and Its Applications in Big Data.
Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Jeffreys Divergence and Generalized Fisher Information Measures on Fokker-Planck Space-Time Random Field.Entropy (Basel, Switzerland) · 2023Article
- Entropy Analysis of a Flexible Markovian Queue with Server Breakdowns.Entropy (Basel, Switzerland) · 2020Article
- Storage Space Allocation Strategy for Digital Data with Message Importance.Entropy (Basel, Switzerland) · 2020Article
- Attention to the Variation of Probabilistic Events: Information Processing with Message Importance Measure.Entropy (Basel, Switzerland) · 2019Article
- Matching Users' Preference under Target Revenue Constraints in Data Recommendation Systems.Entropy (Basel, Switzerland) · 2019Article
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Authors and funding
3 authors.
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Abstract
Information transfer that characterizes the information feature variation can have a crucial impact on big data analytics and processing. Actually, the measure for information transfer can reflect the system change from the statistics by using the variable distributions, similar to Kullback-Leibler (KL) divergence and Renyi divergence. Furthermore, to some degree, small probability events may carry the most important part of the total message in an information transfer of big data. Therefore, it is significant to propose an information transfer measure with respect to the message importance from the viewpoint of small probability events. In this paper, we present the message importance transfer measure (MITM) and analyze its performance and applications in three aspects. First, we discuss the robustness of MITM by using it to measuring information distance. Then, we present a message importance transfer capacity by resorting to the MITM and give an upper bound for the information transfer process with disturbance. Finally, we apply the MITM to discuss the queue length selection, which is the fundamental problem of caching operation on mobile edge computing.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.