How novel actors achieve a positive reputation: A case of prep schools with elite‐level hockey programs

How are novel organizations able to build a positive reputation while attempting to enter into a system with established organizations? To address this, we examined the field of elite‐level amateur hockey. Private Secondary Schools (PSS) are novel in that they offer a nontraditional pathway for players with respect to fielding elite‐level hockey teams. Findings from interviews with PSS with elite‐level hockey programs revealed that PSS highlight their Selection Processes, Player Development Practices, and the enhanced Player Experience in an effort to build a positive reputation. This study contributes to the literature on reputation by showing that novel organizations can build a reputation through highlighting the unique value they add. Copyright © 2016 ASAC. Published by John Wiley & Sons, Ltd.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Crowdsourcing-based semantic relation recognition for natural language questions over RDF data

ABSTRACT

Natural language query systems over RDF data need to rely on the semantic relations in query. First, we propose the new crowdsourcing model that used to produce semantic relations dataset. The model not only inherits completeness of the iterative model and accuracy of the parallel model, but also saves human resources. Second, we mine the rules of semantic relation recognition from the correlations between dependency structures and semantic relations. Third, we propose an algorithm of semantic relation recognition for natural language query over RDF data, and experiments demonstrate that it can recognize more semantic relations than existing methods.     

中国国有企业改革：经验、困境与出路*

作为国有企业产权改革主要模式，“混合所有制”改革是否有助于确保国有资产保值增值，是否有助于推动中国经济可持续发展等问题仍存在探讨空间。本文基于对于改革开放以来中国国有企业改革的成就和教训的考察，指出“混合所有制”可以作为竞争性部门国有企业改革的一个过渡形式；对于垄断央企的改革应该充分借鉴国际上自然垄断行业的改革经验，打破行政垄断，推动竞争性框架建立，并切实实现从“管企业”逐步调整为“管资本”，通过改革实现国有资产的保值增值，并为经济创造新的增长点。     

各向异性厚板固有频率的精确解

该文抛弃薄板理论的位移和应力假设，利用矩阵分析和三维弹性动力学理论，导出四边简支各向异性厚板的固有频率方程。该方法可推广应用于各向异性层合板动力分析。     

试论生态林业系统的时空观

生态林业系统具有时间、空间两个序列的开发前景。长周期,大跨度的生态林业生产可以分解为复合的短周期方式,使生态意识与经济效益有机结合。空间组合的多层次立体开发有效地利用了光、热、水、土资源,并获得最大生物量;地域组合着眼宏观,注重研究大型骨干及网络性生态工程问题。     

信息不对称对林产品经营影响的分析

探讨了信息不对称现象对林产品经营的影响问题,阐述了林产品市场信息不对称的内涵、基本表征、成因及其对林产品经营的具体影响,提出了林产品经营的新对策:一是加强林产品市场调研,充分掌握市场信息;二是注重林产品信息的传播与扩散;三是讲求诚信经营,努力培养商誉;四是积极实施林产品的标准化经营;五是大力推行林产品的认证经营。     

西气东输工程用感应加热弯管技术条件探讨

在对国外X70管线弯管技术条件进行调查分析与研究的基础上，对其中的几个关键技术问题包括母管成分，弯管的制造工艺和技术路线，强度与韧性要求，屈强比，Cu污染问题等进行了讨论。一些观点在西气东输感应加弯管技术条件中得到应用。     

林产品市场模型文献综述

关于林产品市场的数量研究开始于上个世纪50年代。早期的研究主要以时间序列数据为主。近几十年来,由于经济理论在林产品市场模型中的应用,模型估计方法的改进,以及详细数据的获得,林产品市场模型越来越完善。文章对近几十年来出现的主要建模方法,及其应用作一回顾,并对这些方法的优缺点作简单的比较。