TEG—a hybrid approach to information extraction

This paper describes a hybrid statistical and knowledge-based information extraction model, able to extract entities and relations at the sentence level. The model attempts to retain and improve the high accuracy levels of knowledge-based systems while drastically reducing the amount of manual labour by relying on statistics drawn from a training corpus. The implementation of the model, called TEG (trainable extraction grammar), can be adapted to any IE domain by writing a suitable set of rules in a SCFG (stochastic context-free grammar)-based extraction language and training them using an annotated corpus. The system does not contain any purely linguistic components, such as PoS tagger or shallow parser, but allows to using external linguistic components if necessary. We demonstrate the performance of the system on several named entity extraction and relation extraction tasks. The experiments show that our hybrid approach outperforms both purely statistical and purely knowledge-based systems, while requiring orders of magnitude less manual rule writing and smaller amounts of training data. We also demonstrate the robustness of our system under conditions of poor training-data quality. Ronen Feldman is a senior lecturer at the Mathematics and Computer Science Department of Bar-Ilan University in Israel, and the Director of the Data Mining Laboratory. He received his B.Sc. in Math, Physics and Computer Science from the Hebrew University, M.Sc. in Computer Science from Bar-Ilan University, and his Ph.D. in Computer Science from Cornell University in NY. He was an Adjunct Professor at NYU Stern Business School. He is the founder of ClearForest Corporation, a Boston based company specializing in development of text mining tools and applications. He has given more than 30 tutorials on next mining and information extraction and authored numerous papers on these topics. He is currently finishing his book “The Text Mining Handbook” to the published by Cambridge University Press. Benjamin Rosenfeld is a research scientist at ClearForest Corporation. He received his B.Sc. in Mathematics and Computer Science from Bar-Ilan University. He is the co-inventor of the DIAL information extraction language. Moshe Fresko is finalizing his Ph.D. in Computer Science Department at Bar-Ilan University in Israel. He received his B.Sc. in Computer Engineering from Bogazici University, Istanbul/Turkey on 1991, and M.Sc. on 1994. He is also an adjunct lecturer at the Computer Science Department of Bar-Ilan University and functions as the Information-Extraction Group Leader in the Data Mining Laboratory.     

Graphical model construction based on evolutionary algorithms

Using Bayesian networks to model promising solutions from the current population of the evolutionary algorithms can ensure efficiency and intelligence search for the optimum. However, to construct a Bayesian network that fits a given dataset is a NP-hard problem, and it also needs consuming mass computational resources. This paper develops a methodology for constructing a graphical model based on Bayesian Dirichlet metric. Our approach is derived from a set of propositions and theorems by researching the local metric relationship of networks matching dataset. This paper presents the algorithm to construct a tree model from a set of potential solutions using above approach. This method is important not only for evolutionary algorithms based on graphical models, but also for machine learning and data mining. The experimental results show that the exact theoretical results and the approximations match very well.     

Delay‐dependent fault estimation for uncertain time‐delay nonlinear systems: an LMI approach

This paper deals with the problem of robust fault estimation for uncertain time‐delay Takagi–Sugeno (TS) fuzzy models. The aim of this study is to design a delay‐dependent fault estimator ensuring a prescribed ??_∞ performance level for the fault estimation error, irrespective of the uncertainties and the time delays. Sufficient conditions for the existence of a robust fault estimator are given in terms of linear matrix inequalities (LMIs). Membership functions' (MFs) characteristics are incorporated into the fault estimator design to reduce the conservativeness of neglecting these characteristics. Finally, a numerical example is given to illustrate the effectiveness of the proposed design techniques. Copyright © 2006 John Wiley & Sons, Ltd.     

Bayesian testing for non-linearity in volatility modeling

Neural networks provide a tool for describing non-linearity in volatility processes of financial data and help to answer the question “how much” non-linearity is present in the data. Non-linearity is studied under three different specifications of the conditional distribution: Gaussian, Student-t and mixture of Gaussians. To rank the volatility models, a Bayesian framework is adopted to perform a Bayesian model selection within the different classes of models. In the empirical analysis, the return series of the Dow Jones Industrial Average index, FTSE 100 and NIKKEI 225 indices over a period of 16 years are studied. The results show different behavior across the three markets. In general, if a statistical model accounts for non-normality and explains most of the fat tails in the conditional distribution, then there is less need for complex non-linear specifications.     

Air cargo pickup schedule for single delivery location

In this paper, various deterministic models for determining optimal pickup times for air cargo from an airport and delivering it to a local distribution center for a global manufacturer are presented. The arrival times of the flights that can potentially bring air cargo are assumed to be deterministic and known. In addition, the custom clearance time for the air cargo and the traveling time from the airport to the local distribution center are assumed to be deterministic and known. These models are formulated mathematically as linear binary integer programming models without air cargo weight considerations. Deterministic formulations without air cargo weight information are shown to be related to the p-Median problem. The deterministic formulation of air cargo pickup times with air cargo weight consideration is shown to be a nonlinear binary integer programming model. The solutions of these models serve as an initial starting point to solve the stochastic problem with random arrival times of the flights and random custom clearance times and travel times.     

Inflatable Models

A physically-based model is presented for the simulation of a new type of deformable objects-inflatable objects, such as shaped balloons, which consist of pressurized air enclosed by an elastic surface. These objects have properties inherent in both 3D and 2D elastic bodies, as they demonstrate the behaviour of 3D shapes using 2D formulations. As there is no internal structure in them, their behaviour is substantially different from the behaviour of deformable solid objects. We use one of the few available models for deformable surfaces, and enhance it to include the forces of internal and external pressure. These pressure forces may also incorporate buoyancy forces, to allow objects filled with a low density gas to float in denser media. The obtained models demonstrate rich dynamic behaviour, such as bouncing, floating, deflation and inflation.     

Relationships among team ability composition, team mental models, and team performance.

This study examined the relationship between the similarity and accuracy of team mental models and compared the extent to which each predicted team performance. The relationship between team ability composition and team mental models was also investigated. Eighty-three dyadic teams worked on a complex skill task in a 2-week training protocol. Results indicated that although similarity and accuracy of team mental models were significantly related, accuracy was a stronger predictor of team performance. In addition, team ability was more strongly related to the accuracy than to the similarity of team mental models and accuracy partially mediated the relationship between team ability and team performance, but similarity did not. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Relations between neighborhood factors, parenting behaviors, peer deviance, and delinquency among serious juvenile offenders.

The present study examined relations among neighborhood structural and social characteristics, parenting practices, peer group affiliations, and delinquency among a group of serious adolescent offenders. The sample of 14-18-year-old boys (N = 488) was composed primarily of economically disadvantaged, ethnic-minority youth living in urban communities. The results indicate that weak neighborhood social organization is indirectly related to delinquency through its associations with parenting behavior and peer deviance and that a focus on just 1 of these microsystems can lead to oversimplified models of risk for juvenile offending. The authors also find that community social ties may confer both pro- and antisocial influences to youth, and they advocate for a broad conceptualization of neighborhood social processes as these relate to developmental risk for youth living in disadvantaged communities. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A model of stage of change to recommend colonoscopy among urban primary care physicians.

Theory is little used in the prediction of physician cancer screening stage of change. Structural equation modeling was used to evaluate the theoretical predictors of stage of change to recommend colonoscopy among 235 urban physicians. Constructs from the theory of planned behavior, social-cognitive theory, and the transtheoretical model were systematically tested. As predicted, contextual factors, such as the physicians' ages, their race-ethnicities, patient race-ethnicity, and office-related barriers to preventive care were associated with stage of change through self-efficacy, normative beliefs, and negative behavioral beliefs. The findings demonstrate the relevance of these models to studying the behavior of physicians and support the development of interventions that are tailored to normative beliefs and specific physician cognitions for colonoscopy recommendation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Paper and plastic in daily diary research: Comment on Green, Rafaeli, Bolger, Shrout, and Reis (2006).

The authors applaud A. S. Green, E. Rafaeli, N. Bolger, P. E. Shrout, and H. T. Reis's (2006) response to one-sided comparisons of paper versus electronic (plastic) diary methods (see record 2006-03820-006) and hope that it will stimulate more balanced considerations of the issues involved. The authors begin by highlighting areas of agreement and disagreement with Green et al. The authors review briefly the broader literature that has compared paper and plastic diaries, noting how recent comparisons have relied on study designs and methods that favor investigators' allegiances. The authors note some sorely needed data for the evaluation of the implications of paper versus plastic for the internal and external validity of research. To facilitate evaluation of the existing literature and assist in the design of future studies, the authors offer a balanced comparison of paper and electronic diary methods across a range of applications. Finally, the authors propose 2 study designs that offer fair comparisons of paper and plastic diary methods. (PsycINFO Database Record (c) 2010 APA, all rights reserved)