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.     

Information and Knowledge as Antecedents of Consumer Attitudes and Intentions to Buy and Recommend Fair-Trade Products

The authors propose and empirically test a causal model to understand how the availability of fair-trade information and consumer knowledge about this issue affect consumers’ attitudes and intentions toward fair-trade products. The model is built upon the attitude-behavior paradigm and the premises of agency theory. It is tested through structural equation modeling with a sample of 292 Spanish consumers. The findings are that consumers do not have good knowledge about fair trade and that this is significantly determined by the lack of information about this in the market. It is also observed that consumers’ perceptions about the availability of fair-trade information have negative effects on their concern about this issue and that such information as is available is not effective in reducing consumer skepticism. The research represents an extension of previous fair-trade literature because the role of information and communication in improving consumer attitudes and buying intentions has rarely been explored in the case of ethical products.     

干预行为——经济法中的“法律行为”

在我国法学界,"法律行为"有两种不同含义,一是民法上的含义,意指意思效果行为。这也是法律行为的原初含义。另一是法理学上的含义,意指具有法律效果的行为。经济法的法律行为应采何意?从相关的论述看,多是在法理学意义上使用的。笔者之见,法律行为应回归其原初含义,而最能反映经济法特征的法律行为就是"干预行为",即公共经济组织的"公意"表示及执行行为,包括宏观调控和市场规制行为。     

基本建设投资领域"项目"名词的考证

“项目”一词及其派生词组在基本建设投资领域中的引用非常频繁,由于没有对其进行行业的规范定义,所以使用中常出现混乱,造成词义的误解。通过对“项目”名词的考证,分析了“项目”各种组合名词的内涵限定意义和层次关系,提出了在基本建设投资领域内对“项目”一词及其派生词组的含义认知应统一的意见。     

关于少数民族汉语词汇教学中新词新义的思考

当代汉语词汇产生了7000条左右新词语,但在少数民族汉语教学中较少接触。应尽快研制少数民族汉 语教学大纲,并给予相应的教学安排,以便进一步提高少数民族汉语教学质量。     

跨文化词义的比较与翻译

词汇是语言符号和体言中的最小的有意义的语言载体,对跨文化词义的社会性、文化性、民族化、地理环境和喻体相异性、习俗的文化意义等进行比较,有助于跨文化翻译.采用异化法、异化解释法、归化法、归化意译法等方法,将翻译置于跨文化交际中进行,以达到跨文化交际中的文化效应最大近似或对应.     

翻译中词义的理解与表达

翻译中词义的理解与表达起着重要的作用。基于奈达的翻译理论，从英汉互译的角度，通过一些翻译实例，阐明只有正确把握词汇的多义性以及字词在不同文体中的最佳表达，才能使翻译成为一种成功的再创作。     

汉英颜色词的异同对比及分析

中英文化历史悠久,两种文化背景下颜色词的起源、发展演变、语义及运用,既有相同之处,也存在着很大的差异.通过汉英对比的方法,对汉英两种语言中的部分颜色词的语言特点、文化意义的异同进行比较,可以帮助我们更好地理解和运用语言及其文化.     

宏观投资的影响因素与实证分析

在界定宏观投资的基础上，选择储蓄、价格、利润和利率等影响因素的代表变量，建立固定资产投资的理论模型；以1985－1999年为样本区间，采用SPSS统计分析软件包，对变量数据进行相关性分析和主成分分析，构建我国固定资产投资的回归模型；通过实证分析得出我国固定资产投资各影响因素的结论并给出相应的政策含义。     

浅析语篇教学

语篇教学越来越受到大学英语教师的重视,其作用也越来越显现。本文从语篇教学的内容、特点、具体操作过程及教学意义等几方面对语篇教学进行了阐述。