A Knowledge Fusion Model for Web Information

A semantic-based knowledge fusion model for solution-oriented information network development: a case study in intrusion detection field

Scientometrics ◽

10.1007/s11192-018-2904-6 ◽

2018 ◽

Vol 117 (2) ◽

pp. 857-886 ◽

Cited By ~ 4

Author(s):

Yu Zhang ◽

Morteza Saberi ◽

Elizabeth Chang

Keyword(s):

Intrusion Detection ◽

Information Network ◽

Network Development ◽

Fusion Model ◽

Knowledge Fusion

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Research on multi-sources knowledge fusion model for industrial innovative design

Proceedings of the 2016 International Conference on Advances in Management, Arts and Humanities Science ◽

10.2991/amahs-16.2016.44 ◽

2016 ◽

Author(s):

Wei Liu ◽

Shuai Liu ◽

Limeng Liu ◽

Runhua Tan

Keyword(s):

Fusion Model ◽

Innovative Design ◽

Knowledge Fusion

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Rule-Based Agricultural Knowledge Fusion in Web Information Integration

Sensor Letters ◽

10.1166/sl.2012.1874 ◽

2012 ◽

Vol 10 (1) ◽

pp. 635-638 ◽

Cited By ~ 2

Author(s):

Xie Nengfu ◽

Wang Wensheng ◽

Yang Xiaorong ◽

Jiang Lihua

Keyword(s):

Information Integration ◽

Rule Based ◽

Knowledge Fusion ◽

Agricultural Knowledge ◽

Web Information

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Utilization of Automatic Tagging Using Web Information to Datamining

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.132.623 ◽

2012 ◽

Vol 132 (4) ◽

pp. 623-624

Author(s):

Hiroshi Sugimura ◽

Kazunori Matsumoto

Keyword(s):

Web Information ◽

Automatic Tagging

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An Accelerated Cue Combination Principle Accounts for Multi-cue Depth Perception

Journal of Perceptual Imaging ◽

10.2352/j.percept.imaging.2020.3.1.010501 ◽

2020 ◽

Vol 3 (1) ◽

pp. 10501-1-10501-9

Author(s):

Christopher W. Tyler

Keyword(s):

Belief Propagation ◽

Probability Distributions ◽

Three Dimensional ◽

Dimensional Structure ◽

Fusion Model ◽

Cue Combination ◽

Depth Estimate ◽

Appropriate Behavior ◽

Depth Cues ◽

Bayesian Averaging

Abstract For the visual world in which we operate, the core issue is to conceptualize how its three-dimensional structure is encoded through the neural computation of multiple depth cues and their integration to a unitary depth structure. One approach to this issue is the full Bayesian model of scene understanding, but this is shown to require selection from the implausibly large number of possible scenes. An alternative approach is to propagate the implied depth structure solution for the scene through the “belief propagation” algorithm on general probability distributions. However, a more efficient model of local slant propagation is developed as an alternative.The overall depth percept must be derived from the combination of all available depth cues, but a simple linear summation rule across, say, a dozen different depth cues, would massively overestimate the perceived depth in the scene in cases where each cue alone provides a close-to-veridical depth estimate. On the other hand, a Bayesian averaging or “modified weak fusion” model for depth cue combination does not provide for the observed enhancement of perceived depth from weak depth cues. Thus, the current models do not account for the empirical properties of perceived depth from multiple depth cues.The present analysis shows that these problems can be addressed by an asymptotic, or hyperbolic Minkowski, approach to cue combination. With appropriate parameters, this first-order rule gives strong summation for a few depth cues, but the effect of an increasing number of cues beyond that remains too weak to account for the available degree of perceived depth magnitude. Finally, an accelerated asymptotic rule is proposed to match the empirical strength of perceived depth as measured, with appropriate behavior for any number of depth cues.

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A Walk through Various Data Hiding Techniques

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i8.20 ◽

2017 ◽

Vol 7 (8) ◽

pp. 52

Author(s):

Manoj Kumar ◽

Rohit Tanwar

Keyword(s):

Data Hiding ◽

Data Framework ◽

Web Information ◽

Fundamental Part ◽

Secure Information ◽

Numerous Data ◽

Security Information ◽

Security Procedures

In the computerized age as a result of the broad utilization of web, information covering up in advanced symbolism assumes a fundamental part to guarantee copyright assurance and power from pernicious assaults. Today the exponential development in web clients request secure information correspondence, for that it is required to send the information as encoded or shrouded shape. Numerous data framework security procedures are accessible.Information transmission needs security. Information covering up can be accomplished through numerous techniques. Distinctive information concealing procedures are talked about in this paper which incorporates watermarking, steganography, fingerprinting, cryptography and advanced mark.

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