Chapter 11 – Further readings

This chapter provides readers with further readings in related areas of this book. These areas are closely related with the problems, theories, and techniques that are reviewed in the book. Readers are recommended to take the material presented in this chapter as references if they want to explore related problems from a broader perspective. Examples of the reviewed areas in this chapter include: estimation theory, data quality and trust analysis, outlier analysis and attack detection, recommender systems, surveys, and opinion polling.

[1]  Yang Wang,et al.  Personalization and privacy: a survey of privacy risks and remedies in personalization-based systems , 2012, User Modeling and User-Adapted Interaction.

[2]  Michel Fattouche,et al.  OFDM Transmission for Time-Based Range Estimation , 2010, IEEE Signal Processing Letters.

[3]  Rafael Weißbach,et al.  Asymptotic normality for discretely observed Markov jump processes with an absorbing state , 2014 .

[4]  Erhard Rahm,et al.  Frameworks for entity matching: A comparison , 2010, Data Knowl. Eng..

[5]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[6]  Xiao-Ping Zhang,et al.  A Novel Location-Penalized Maximum Likelihood Estimator for Bearing-Only Target Localization , 2012, IEEE Transactions on Signal Processing.

[7]  Michael Kaminsky,et al.  SybilGuard: defending against sybil attacks via social networks , 2006, SIGCOMM.

[8]  R. Gardner,et al.  Using Amazon's Mechanical Turk website to measure accuracy of body size estimation and body dissatisfaction. , 2012, Body image.

[9]  Victoria J. Hodge,et al.  A Survey of Outlier Detection Methodologies , 2004, Artificial Intelligence Review.

[10]  Peter J. Bickel,et al.  Community Detection in Networks using Graph Distance , 2014, ArXiv.

[11]  Jeffrey R. Lax,et al.  How Should We Estimate Public Opinion in the States , 2009 .

[12]  Gediminas Adomavicius,et al.  New Recommendation Techniques for Multicriteria Rating Systems , 2007, IEEE Intelligent Systems.

[13]  Mark E. J. Newman,et al.  An efficient and principled method for detecting communities in networks , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  Erhard Rahm,et al.  A survey of approaches to automatic schema matching , 2001, The VLDB Journal.

[15]  Hong Qin,et al.  Asymptotic normality in the maximum entropy models on graphs with an increasing number of parameters , 2013, J. Multivar. Anal..

[16]  Xiangyu Chang,et al.  Asymptotic Normality of Maximum Likelihood and its Variational Approximation for Stochastic Blockmodels , 2012, ArXiv.

[17]  King-wa Fu,et al.  Analyzing Online Sentiment to Predict Telephone Poll Results , 2013, Cyberpsychology Behav. Soc. Netw..

[18]  Shu Hung Leung,et al.  Damped sinusoidal signals parameter estimation in frequency domain , 2012, Signal Process..

[19]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[20]  Jingbo Zhu,et al.  Aspect-Based Opinion Polling from Customer Reviews , 2011, IEEE Transactions on Affective Computing.

[21]  Ian A. Wood,et al.  Asymptotic Normality of the Maximum Pseudolikelihood Estimator for Fully Visible Boltzmann Machines , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[22]  Stephen Soderland,et al.  Learning Information Extraction Rules for Semi-Structured and Free Text , 1999, Machine Learning.