scholarly journals On the depth of decision trees over infinite 1-homogeneous binary information systems

Array ◽  
2021 ◽  
pp. 100060
Author(s):  
Mikhail Moshkov
Keyword(s):  
Information Systems ◽  
Decision Trees ◽  
Binary Information

scholarly journals On the Depth of Decision Trees with Hypotheses

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 116
Author(s):  
Mikhail Moshkov
Keyword(s):  
Information Systems ◽  
Decision Trees ◽  
Rough Set Theory ◽  
Test Theory ◽  
Complexity Classes ◽  
Worst Case ◽  
Exact Learning ◽  
Equivalence Queries ◽  
Problem Description ◽  
Binary Information

In this paper, based on the results of rough set theory, test theory, and exact learning, we investigate decision trees over infinite sets of binary attributes represented as infinite binary information systems. We define the notion of a problem over an information system and study three functions of the Shannon type, which characterize the dependence in the worst case of the minimum depth of a decision tree solving a problem on the number of attributes in the problem description. The considered three functions correspond to (i) decision trees using attributes, (ii) decision trees using hypotheses (an analog of equivalence queries from exact learning), and (iii) decision trees using both attributes and hypotheses. The first function has two possible types of behavior: logarithmic and linear (this result follows from more general results published by the author earlier). The second and the third functions have three possible types of behavior: constant, logarithmic, and linear (these results were published by the author earlier without proofs that are given in the present paper). Based on the obtained results, we divided the set of all infinite binary information systems into four complexity classes. In each class, the type of behavior for each of the considered three functions does not change.

Cost Containment in Information Systems

1984 ◽  
Vol 1 (1) ◽  
pp. 175-185
Author(s):  
Michael E. D. Koenig
Keyword(s):  
Information Systems ◽  
Cost Containment

Trust in Management Information Systems (MIS)

2020 ◽  
Vol 64 (1) ◽  
pp. 6-16 ◽  
Author(s):  
Sarah M. Meeßen ◽  
Meinald T. Thielsch ◽  
Guido Hertel
Keyword(s):  
Information Systems ◽  
Information Overload ◽  
Management Information Systems ◽  
Empirical Work ◽  
Future Research ◽  
Management Information ◽  
Trust In Management ◽  
Actual Use ◽  
Trust In Technology ◽  
The Internet Of Things

Abstract. Digitalization, enhanced storage capacities, and the Internet of Things increase the volume of data in modern organizations. To process and make use of these data and to avoid information overload, management information systems (MIS) are introduced that collect, process, and analyze relevant data. However, a precondition for the application of MIS is that users trust them. Extending accounts of trust in automation and trust in technology, we introduce a new model of trust in MIS that addresses the conceptual ambiguities of existing conceptualizations of trust and integrates initial empirical work in this field. In doing so, we differentiate between perceived trustworthiness of an MIS, experienced trust in an MIS, intentions to use an MIS, and actual use of an MIS. Moreover, we consider users’ perceived risks and contextual factors (e. g., autonomy at work) as moderators. The introduced model offers guidelines for future research and initial suggestions to foster trust-based MIS use.

How Are Questions and Information Systems Related?

1993 ◽  
Vol 38 (10) ◽  
pp. 1094-1095
Author(s):  
Scott P. Robertson
Keyword(s):  
Information Systems
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