Crime profiling for the Arabic language using computational linguistic techniques     

Meshrif Alruily  Aladdin Ayesh  Hussein Zedan 《Information processing & management》2014

Arabic is a widely spoken language but few mining tools have been developed to process Arabic text. This paper examines the crime domain in the Arabic language (unstructured text) using text mining techniques. The development and application of a Crime Profiling System (CPS) is presented. The system is able to extract meaningful information, in this case the type of crime, location and nationality, from Arabic language crime news reports. The system has two unique attributes; firstly, information extraction that depends on local grammar, and secondly, dictionaries that can be automatically generated. It is shown that the CPS improves the quality of the data through reduction where only meaningful information is retained. Moreover, the Self Organising Map (SOM) approach is adopted in order to perform the clustering of the crime reports, based on crime type. This clustering technique is improved because only refined data containing meaningful keywords extracted through the information extraction process are inputted into it, i.e. the data are cleansed by removing noise. The proposed system is validated through experiments using a corpus collated from different sources; it was not used during system development. Precision, recall and F-measure are used to evaluate the performance of the proposed information extraction approach. Also, comparisons are conducted with other systems. In order to evaluate the clustering performance, three parameters are used: data size, loading time and quantization error.  相似文献   

Using compositional semantics and discourse consistency to improve Chinese trigger identification     

Pei-Feng Li  Qiao-Ming Zhu  Guo-Dong Zhou 《Information processing & management》2014

Due to the special characteristics and challenges in Chinese language, event extraction in Chinese is much more difficult than that in English. In particular, the state-of-the-art Chinese event extraction systems suffer much from the low recall in trigger identification due to the failure in identifying unknown triggers and the inconsistency in identifying trigger mentions. To resolve these two issues, this paper proposes an inference mechanism to infer unknown triggers via the compositional semantics inside Chinese words and another inference mechanism to recover trigger mentions via the discourse consistency between Chinese trigger mentions. Here, various morphological structures are explored to better represent the compositional semantics inside Chinese triggers and automatically identify the head morpheme as the governing sememe of a trigger in inferring unknown triggers. Evaluation on the ACE 2005 Chinese corpus justifies the effectiveness of our approach over a strong baseline in Chinese event extraction, in particular trigger identification.  相似文献   

BizPro: Extracting and categorizing business intelligence factors from textual news articles     

《International Journal of Information Management》2014,34(2):272-284

Company movements and market changes often are headlines of the news, providing managers with important business intelligence (BI). While existing corporate analyses are often based on numerical financial figures, relatively little work has been done to reveal from textual news articles factors that represent BI. In this research, we developed BizPro, an intelligent system for extracting and categorizing BI factors from news articles. BizPro consists of novel text mining procedures and BI factor modeling and categorization. Expert guidance and human knowledge (with high inter-rater reliability) were used to inform system development and profiling of BI factors. We conducted a case study of using the system to profile BI factors of four major IT companies based on 6859 sentences extracted from 231 news articles published in major news sources. The results show that the chosen techniques used in BizPro – Naïve Bayes (NB) and Logistic Regression (LR) – significantly outperformed a benchmark technique. NB was found to outperform LR in terms of precision, recall, F-measure, and area under ROC curve. This research contributes to developing a new system for profiling company BI factors from news articles, to providing new empirical findings to enhance understanding in BI factor extraction and categorization, and to addressing an important yet under-explored concern of BI analysis.  相似文献   

Soft-constrained inference for Named Entity Recognition     

E. Fersini  E. Messina  G. Felici  D. Roth 《Information processing & management》2014

Much of the valuable information in supporting decision making processes originates in text-based documents. Although these documents can be effectively searched and ranked by modern search engines, actionable knowledge need to be extracted and transformed in a structured form before being used in a decision process. In this paper we describe how the discovery of semantic information embedded in natural language documents can be viewed as an optimization problem aimed at assigning a sequence of labels (hidden states) to a set of interdependent variables (textual tokens). Dependencies among variables are efficiently modeled through Conditional Random Fields, an indirected graphical model able to represent the distribution of labels given a set of observations. The Markov property of these models prevent them to take into account long-range dependencies among variables, which are indeed relevant in Natural Language Processing. In order to overcome this limitation we propose an inference method based on Integer Programming formulation of the problem, where long distance dependencies are included through non-deterministic soft constraints.  相似文献   

The impact of preprocessing on text classification     

Alper Kursat Uysal  Serkan Gunal 《Information processing & management》2014

Preprocessing is one of the key components in a typical text classification framework. This paper aims to extensively examine the impact of preprocessing on text classification in terms of various aspects such as classification accuracy, text domain, text language, and dimension reduction. For this purpose, all possible combinations of widely used preprocessing tasks are comparatively evaluated on two different domains, namely e-mail and news, and in two different languages, namely Turkish and English. In this way, contribution of the preprocessing tasks to classification success at various feature dimensions, possible interactions among these tasks, and also dependency of these tasks to the respective languages and domains are comprehensively assessed. Experimental analysis on benchmark datasets reveals that choosing appropriate combinations of preprocessing tasks, rather than enabling or disabling them all, may provide significant improvement on classification accuracy depending on the domain and language studied on.  相似文献   

白桦脂醇的提取纯化工艺研究     

卢福强  魏凯 《黑龙江科技信息》2014,(2):54-54

目的:以白桦树皮为原料,研究了白桦树皮中白桦脂醇提取和纯化的工艺,并使此工艺适合药用放大生产。方法:使用乙醇提取,使用乙酸乙酯和不同浓度的乙醇进行精制。结果:所得到的精制品经过高效液相检验含量在98%以上。结论:白桦脂醇的提取纯化过程中使用的都是常规的可操作方法,适合放大生产。  相似文献   

黄酮类化合物研究进展     

代雄  颜杰宽  甘秀海 《贵州教育学院学报》2013,(9):38-42

黄酮类化合物是具有多种药理作用的植物次生代谢产物,广泛存在于中草药中,由于其具有抗肿瘤、抗氧化及抗茵等活性,日益受到国内外学者的关注。为了更好地开发和利用其资源,综述了近年来黄酮类化合物提取工艺、药理作用、合成及临床应用等方面的研究进展。  相似文献   

基于列选主QR分解和节约型SVD的直接线性鉴别分析     

胡长晖  路小波  杜一君  陈伍军 《东南大学学报》2013,(4):395-399

针对传统DLDA算法计算复杂的问题,提出了DLDA／ESVD算法,该算法直接使用ESVD降维和提取非零特征值对应的特征向量．然后,为了提高DLDA／ESVD算法处理高维低秩矩阵的性能,提出了DL—DA／QR—ESVD算法,该算法使用列选主QR分解降维,使用ESVD提取非零特征值对应的特征向量．在ORL,FERET和YALE数据库上的实验结果表明,所提出的2种算法具有几乎相同的性能,并在计算复杂性和训练时间方面优于传统的DLDA算法．另外,在随机数据矩阵上的实验结果表明,DLDA／QR—ESVD算法处理高维低秩矩阵的性能优于DLDA／ESVD算法．  相似文献   

固相萃取-UPLC—MS／MS测定食品中的黄曲霉毒素M1和B1     

肖丽恒  何学梅  李萍  谢启明 《楚雄师专学报》2013,(9):49-52

建立固相萃取与UPLC—MS／MS检测食品中黄曲霉毒素M1和黄曲霉毒素B1的方法。样品经乙腈提取和SPE小柱萃取净化,提取液经氮气吹干后,用50％甲醇水溶液定容。超高效液相色谱一串联质谱（UPLC—MS／MS）测定,采用电喷雾正离子（ESI＋）模式电离,多反应监测（MRM）模式检测。流动相为0．1％甲酸水溶液和甲醇,流速0．4ml／min,使用ZORBAX Eclipse XDB—C18色谱柱（100mm×3．0mm×1．8μm）为分析柱。黄曲霉毒素AFM1在0．1～50μg／kg范围内线性关系良好、黄曲霉毒素AFB1在0．1～10ug／kg范围内线性关系良好,相关系数均大于0．999;回收率在83．75％～97．8％之间;检出限AFMl为0．05μg／kg、AFBl0．02μg／kg。该法具有分析速度快,检测准确、灵敏度和回收率高等优点,适合食品中黄曲霉毒素M1、B1含量的检测。  相似文献   

建设中国开放大学的国家政策文本分析     

杨敏  魏志慧 《现代远程教育研究》2013,(3):98-103

以文本分析或话语分析的手法切入政策研究,已经成为国际上政策研究领域的一种常用方法。政策文本分析是理解中国开放大学政策的基本手段,也是促进我国开放大学建设政策研究和政策执行的重要途径。2012年6月21日,教育部连续签发三个重要批复:同意在中央广播电视大学基础上建立国家开放大学的批复,以及同意北京广播电视大学、上海电视大学分别更名为北京开放大学和上海开放大学的批复。这三个具有代表性的政策文本集中展示了国家教育部门对新型大学建设目标的总体设计,包括建设路径和发展策略的整体设定,对中国开放大学在教育活动、教育体制、教育机制、教育观念等方面给予了指导性定位。概括地说,就是回答了中国开放大学该由谁来办、怎么办、办成什么样的政策问题。这是中国开放大学建设的政策依据和行动纲领,只有准确把握政策目标和行动线路,才能有效推进中国开放大学的历史进程。  相似文献