Knowledge-Augmented Language Model and its Application to Unsupervised Named-Entity Recognition

Traditional language models are unable to efficiently model entity names observed in text. All but the most popular named entities appear infrequently in text providing insufficient context. Recent efforts have recognized that context can be generalized between entity names that share the same type (e.g., \emph{person} or \emph{location}) and have equipped language models with access to an external knowledge base (KB). Our Knowledge-Augmented Language Model (KALM) continues this line of work by augmenting a traditional model with a KB. Unlike previous methods, however, we train with an end-to-end predictive objective optimizing the perplexity of text. We do not require any additional information such as named entity tags. In addition to improving language modeling performance, KALM learns to recognize named entities in an entirely unsupervised way by using entity type information latent in the model. On a Named Entity Recognition (NER) task, KALM achieves performance comparable with state-of-the-art supervised models. Our work demonstrates that named entities (and possibly other types of world knowledge) can be modeled successfully using predictive learning and training on large corpora of text without any additional information.Comment: NAACL 2019; updated to cite Zhou et al. (2018) EMNLP as a piece of related wor

Development and preliminary validation of multidimensional life satisfaction of internal migrant workers' children in China

Background Internal labor exporting in China has been a common phenomenon, more and more people from rural area of China migrant to cities for jobs, which leads to the unavoidable social situation of left-behind and migrant children. Research has been focusing on the negative influences on these groups of children, while my research attempted to develop a scale to measure their satisfaction of life. I estimate life satisfaction of my target group from 6 domains: friend, school, living environment, self, material, and family. The items in family domain are different for children who live with both of parents and children who don't live with both of parents. Method I collected data for two rounds. In the first round, only my proposed life satisfaction scale for migrant workers' children was used. Confirmatory factor analysis (CFA) and Exploratory factor analysis (EFA) were used to detect underlaying factors, model fitting criterions such as root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI), and item loading values' criterions are used to eliminate items. In the second round, the adjusted scale was applied, as well as Student Life Satisfaction Scale (SLSS), Self- Description Questionnaire-II (SDQ-II), and Positive and Negative Affect Schedule (PANAS) for validity estimating. McDonald's Omega was used for reliability estimation. Measurement Invariance between groups was also tested. Latent means of different groups were compared. Result The adjusted life satisfaction of internal migrant workers' children scale contains 31 items for each group. McDonald's Omega showed acceptable values for every domain in two groups. Validity evidence can be seen from: my scale can be distinguished from SLSS and PANAS. Domains in my scale and the overall score also can predict global life satisfaction. The correlations between overall score of my scale positively correlated with scores of different domains of SDQ-II. Measurement invariance testing shows measurement invariance between children live with or without both of parents/males and females/being only child or not on configural, scalar and metric levels. Latent mean comparison shows that children who live with both parents have higher life satisfactions in the domains of friends, living environment, and self. In the sample of children who live with both of their parents, boys have less life satisfaction of family, while children who are only child(ren) have a higher life satisfaction of friends. Conclusion A six-domain specific scale of internal migrant workers' children in China was developed and preliminarily validated in this study.Includes bibliographical references

Fast Network Community Detection with Profile-Pseudo Likelihood Methods

The stochastic block model is one of the most studied network models for community detection. It is well-known that most algorithms proposed for fitting the stochastic block model likelihood function cannot scale to large-scale networks. One prominent work that overcomes this computational challenge is Amini et al.(2013), which proposed a fast pseudo-likelihood approach for fitting stochastic block models to large sparse networks. However, this approach does not have convergence guarantee, and is not well suited for small- or medium- scale networks. In this article, we propose a novel likelihood based approach that decouples row and column labels in the likelihood function, which enables a fast alternating maximization; the new method is computationally efficient, performs well for both small and large scale networks, and has provable convergence guarantee. We show that our method provides strongly consistent estimates of the communities in a stochastic block model. As demonstrated in simulation studies, the proposed method outperforms the pseudo-likelihood approach in terms of both estimation accuracy and computation efficiency, especially for large sparse networks. We further consider extensions of our proposed method to handle networks with degree heterogeneity and bipartite properties

Role of ghrelin in promoting catch-up growth and maintaining metabolic homeostasis in small-for-gestational-age infants

Small-for-gestational age (SGA) has been a great concern in the perinatal period as it leads to adverse perinatal outcomes and increased neonatal morbidity and mortality, has an impact on long-term health outcomes, and increases the risk of metabolic disorders, cardiovascular, and endocrine diseases in adulthood. As an endogenous ligand of the growth hormone secretagotor (GHS-R), ghrelin may play an important role in regulating growth and energy metabolic homeostasis from fetal to adult life. We reviewed the role of ghrelin in catch-up growth and energy metabolism of SGA in recent years. In addition to promoting SGA catch-up growth, ghrelin may also participate in SGA energy metabolism and maintain metabolic homeostasis. The causes of small gestational age infants are very complex and may be related to a variety of metabolic pathway disorders. The related signaling pathways regulated by ghrelin may help to identify high-risk groups of SGA metabolic disorders and formulate targeted interventions to prevent the occurrence of adult dwarfism, insulin resistance-related metabolic syndrome and other diseases

Efficient Resources Provisioning Based on Load Forecasting in Cloud

Cloud providers should ensure QoS while maximizing resources utilization. One optimal strategy is to timely allocate resources in a fine-grained mode according to application’s actual resources demand. The necessary precondition of this strategy is obtaining future load information in advance. We propose a multi-step-ahead load forecasting method, KSwSVR, based on statistical learning theory which is suitable for the complex and dynamic characteristics of the cloud computing environment. It integrates an improved support vector regression algorithm and Kalman smoother. Public trace data taken from multitypes of resources were used to verify its prediction accuracy, stability, and adaptability, comparing with AR, BPNN, and standard SVR. Subsequently, based on the predicted results, a simple and efficient strategy is proposed for resource provisioning. CPU allocation experiment indicated it can effectively reduce resources consumption while meeting service level agreements requirements

Peste des Petits Ruminants Virus in Heilongjiang Province, China, 2014

During March 25–May 5, 2014, we investigated 11 outbreaks of peste des petits ruminants in Heilongjiang Province, China. We found that the most likely source of the outbreaks was animals from livestock markets in Shandong. Peste des petits ruminants viruses belonging to lineages II and IV were detected in sick animals