Automatic text summarization based on textual cohesion

This paper presents two different algorithms that derive the cohesion structure in the form of lexical chains from two kinds of language resources HowNet and TongYiCiCiLin. The re-search that connects the cohesion structure of a text to the derivation of its summary is displayed. A novel model of automatic text summarization is devised,based on the data provided by lexical chains from original texts. Moreover,the construction rules of lexical chains are modified accord-ing to characteristics of the knowledge database in order to be more suitable for Chinese summa-rization. Evaluation results show that high quality indicative summaries are produced from Chi-nese texts.     

Web文本内容过滤方法的研究

文章研究了Web文本内容过滤的方法，分析了向量空间模型、关键词匹配算法等关键技术．并详细讨论了Web网页中文本内容过滤方法的实现过程。重点分析了该方法中的修正值选取、关键词权重函数以及过虑策略等方面的不足，提出了一个改进的Web文本内容过滤方法，能够有效降低算法的复杂性，提高性能。     

中文文本分类系统的设计与实现

文章介绍了中文文本分类系统的基本过程及其关键技术,比较和分析Rocchio、朴素贝叶斯(NB)、kNN三种文本分类算法的分类原理,提出了中文文本分类系统的结构模型,并给出了评估方法和实验结果,测试结果表明KNN算法的分类效果最佳。     

On the predictive ability of narrative disclosures in annual reports

We investigate whether narrative disclosures in 10-K and 10K-405 filings contain value-relevant information for predicting market performance. We apply text classification techniques from computer science to machine code text disclosures in a sample of 4280 filings by 1236 firms over five years. Our methodology develops a model using documents and actual performance for a training sample. This model, when applied to documents from a test set, leads to performance prediction. We find that a portfolio based on model predictions earns significantly positive size-adjusted returns, indicating that narrative disclosures contain value-relevant information. Supplementary analyses show that the text classification model captures information not contained in document-level features of clarity, tone and risk sentiment considered in prior research. However, we find that the narrative score is not providing information incremental to traditional predictors such as size, market-to-book and momentum, but rather affects investors’ use of price momentum as a factor that predicts excess returns.