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Advances in Artificial Intelligence

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Cover of 'Advances in Artificial Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 Integrating Information Gathering Interaction into Transfer of Control Strategies in Adjustable Autonomy Multiagent Systems
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    Chapter 2 A Pruning-Based Algorithm for Computing Optimal Coalition Structures in Linear Production Domains
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    Chapter 3 A Smart Home Agent for Plan Recognition
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    Chapter 4 Using Multiagent Systems to Improve Real-Time Map Generation
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    Chapter 5 An Efficient Resource Allocation Approach in Real-Time Stochastic Environment
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    Chapter 6 Satisfaction Equilibrium: Achieving Cooperation in Incomplete Information Games
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    Chapter 7 How Artificial Intelligent Agents Do Shopping in a Virtual Mall: A ‘Believable’ and ‘Usable’ Multiagent-Based Simulation of Customers’ Shopping Behavior in a Mall
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    Chapter 8 A New Profile Alignment Method for Clustering Gene Expression Data
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    Chapter 9 A Classification-Based Glioma Diffusion Model Using MRI Data
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    Chapter 10 Bayesian Learning for Feed-Forward Neural Network with Application to Proteomic Data: The Glycosylation Sites Detection of the Epidermal Growth Factor-Like Proteins Associated with Cancer as a Case Study
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    Chapter 11 Relaxation of Soft Constraints Via a Unified Semiring
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    Chapter 12 Intelligent Information Personalization Leveraging Constraint Satisfaction and Association Rule Methods
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    Chapter 13 On the Quality and Quantity of Random Decisions in Stochastic Local Search for SAT
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    Chapter 14 Simple Support-Based Distributed Search
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    Chapter 15 Modeling Causal Reinforcement and Undermining with Noisy-AND Trees
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    Chapter 16 An Improved LAZY-AR Approach to Bayesian Network Inference
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    Chapter 17 Four-Valued Semantics for Default Logic
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    Chapter 18 Exploiting Dynamic Independence in a Static Conditioning Graph
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    Chapter 19 Probabilistic Melodic Harmonization
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    Chapter 20 Learning Bayesian Networks in Semi-deterministic Systems
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    Chapter 21 Progressive Defeat Paths in Abstract Argumentation Frameworks
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    Chapter 22 Parsing Korean Honorification Phenomena in a Typed Feature Structure Grammar
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    Chapter 23 Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity
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    Chapter 24 Unsupervised Labeling of Noun Clusters
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    Chapter 25 Language Patterns in the Learning of Strategies from Negotiation Texts
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    Chapter 26 Using Natural Language Processing to Assist the Visually Handicapped in Writing Compositions
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    Chapter 27 Text Compression by Syntactic Pruning
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    Chapter 28 Beyond the Bag of Words: A Text Representation for Sentence Selection
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    Chapter 29 Sentiment Tagging of Adjectives at the Meaning Level
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    Chapter 30 Adaptive Fraud Detection Using Benford’s Law
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    Chapter 31 Partial Local FriendQ Multiagent Learning: Application to Team Automobile Coordination Problem
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    Chapter 32 Trace Equivalence Characterization Through Reinforcement Learning
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    Chapter 33 Belief Selection in Point-Based Planning Algorithms for POMDPs
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    Chapter 34 Learning and Evaluation in the Presence of Class Hierarchies: Application to Text Categorization
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    Chapter 35 Adaptive Clustering Algorithms
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    Chapter 36 Classification Based on Logical Concept Analysis
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    Chapter 37 Machine Learning in a Quantum World
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    Chapter 38 A New Attempt to Silhouette-Based Gait Recognition for Human Identification
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    Chapter 39 Learning Naïve Bayes Tree for Conditional Probability Estimation
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    Chapter 40 On the Performance of Chernoff-Distance-Based Linear Dimensionality Reduction Techniques
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    Chapter 41 Discriminative vs. Generative Classifiers for Cost Sensitive Learning
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    Chapter 42 The K Best-Paths Approach to Approximate Dynamic Programming with Application to Portfolio Optimization
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    Chapter 43 Learning Naive Bayes for Probability Estimation by Feature Selection
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    Chapter 44 Lazy Averaged One-Dependence Estimators
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    Chapter 45 Probabilistic Inference Trees for Classification and Ranking
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    Chapter 46 Parameter Estimation of One-Class SVM on Imbalance Text Classification
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    Chapter 47 MITS: A Mixed-Initiative Intelligent Tutoring System for Sudoku
Attention for Chapter 30: Adaptive Fraud Detection Using Benford’s Law
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Chapter title
Adaptive Fraud Detection Using Benford’s Law
Chapter number 30
Book title
Advances in Artificial Intelligence
Published by
Springer, Berlin, Heidelberg, June 2006
DOI 10.1007/11766247_30
Book ISBNs
978-3-54-034628-9, 978-3-54-034630-2

Fletcher Lu, J. Efrim Boritz, Dominic Covvey

Twitter Demographics

The data shown below were collected from the profiles of 15 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 1%
Unknown 72 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 22%
Student > Master 11 15%
Student > Bachelor 9 12%
Researcher 8 11%
Professor 6 8%
Other 14 19%
Unknown 9 12%
Readers by discipline Count As %
Computer Science 27 37%
Business, Management and Accounting 12 16%
Economics, Econometrics and Finance 7 10%
Mathematics 4 5%
Engineering 3 4%
Other 9 12%
Unknown 11 15%