2017
DOI: 10.3390/info8030098
|View full text |Cite
|
Sign up to set email alerts
|

An Information Theory Calculator for Understanding Information and Library Science Applications

Abstract: Abstract:The study of information as proposed in information theory provides a useful tool for studying many aspects of information systems, libraries, and archives. How does a calculator that computes information-theoretic functions contribute to students learning database ideas such as the relationships between various attributes, or columns in a relational database? Understanding the relationships between variables in a professional discipline can be viewed as the core of the discipline, and these informati… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
2
0

Year Published

2020
2020
2021
2021

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 12 publications
0
2
0
Order By: Relevance
“…Based on support vector machine (SVM) classification algorithm, Antoniy et al [11] established an automatic classification model for L&I resources, integrated the sequential minimal optimization (SMO) to effectively improve the classification efficiency, and optimized the classification effect through grid search of the optimal algorithm parameters. Using the realtime information of the L&I resource set during the update, Losee [12] constructed a resource classification model, and verified its feasibility and effectiveness through experiments on multi-source L&I resource data. After exploring deep into the unified management of L&I resources, Tella et al [13] highlighted the importance of resource management to realtime L&I resource classification, and put forward clear standards for resource classification, principles for differentiating between new and old resources, and effective measures to link up the two kinds of resources; in addition, an L&I resource classification system was developed for the unified management of L&I resources, including 4 A-level classes, 12 B-level classes, and 25 C-level classes.…”
Section: Introductionmentioning
confidence: 99%
“…Based on support vector machine (SVM) classification algorithm, Antoniy et al [11] established an automatic classification model for L&I resources, integrated the sequential minimal optimization (SMO) to effectively improve the classification efficiency, and optimized the classification effect through grid search of the optimal algorithm parameters. Using the realtime information of the L&I resource set during the update, Losee [12] constructed a resource classification model, and verified its feasibility and effectiveness through experiments on multi-source L&I resource data. After exploring deep into the unified management of L&I resources, Tella et al [13] highlighted the importance of resource management to realtime L&I resource classification, and put forward clear standards for resource classification, principles for differentiating between new and old resources, and effective measures to link up the two kinds of resources; in addition, an L&I resource classification system was developed for the unified management of L&I resources, including 4 A-level classes, 12 B-level classes, and 25 C-level classes.…”
Section: Introductionmentioning
confidence: 99%
“… 37. Losee, “An Information Theory Calculator for Understanding Information and Library Science Applications,” Information , 8 no. 3 (2017): 98. …”
mentioning
confidence: 99%