A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.     

基于Gabor变换和支持向量机的手写体字符识别算法

针对在手写字符识别中由于书写习惯和风格的不同造成字符模式不稳定的问题,将支持向量机SVM方法用于手写字符的识别.算法首先采用Gabor变换提取手写字符图像的特征参数,然后采用提取的特征训练SVM分类器.再应用SVM分类器分类和判别手写字符.实验表明这种方法具有良好的车牌识别效果,较强的鲁棒性,较大的应用价值.     

基于Gabor变换的嵌入式气表自动识别系统

介绍一种基于嵌入式操作系统WinCE开发的天然气表字符自动识别系统。系统运用区域增长法和最大类间方差法对图像进行字符区域定位及字符分割,提出了将Gabor特征用于气表字符识别并讨论了Gabor滤波器参数优化设置方法。实验表明系统具有良好的识别效果及实时性。     

一种基于BP网的非线性变换信号模式识别算法

为了获取常用超短波信号的特征参数,采取一种非线性变换的方法。根据信号参数的分布信息,对信号特征不够明显的参数进行二次变换,使所有信号的特征参数都具有较好的区分度,并利用BP网对这些特征参数进行识别。大量的仿真实验表明,该方法参数提取容易,计算量较小,在较低信噪比下能够较好地识别常用的超短波信号。识别的信号为2FSK、MSK、QAM、DPSK和FM。     

中文名片识别系统

在实际的商务活动中,名片已经作为一个重要的身份信息载体,使用频繁。然而随着名片数量的增多,管理越来越麻烦。在实际应用中,研究名片识别的方法,介绍一个独立自主开发的中文商务名片识别系统。该系统首先结合实际中的一些具体问题对名片图像进行预处理;然后在传统版面分析技术的基础上针对版面的特点进行版面分析;最后在对分割区域的字符进行识别之后,根据识别结果中的语义和版面分析得到的位置信息对识别结果进行基于知识规则的理解,从而实现了名片的识别。整个系统在实际应用中表现出良好的性能。     

On self-similarity of premonitory patterns in the regions of natural and induced seismicity

Anticipating the scale invariance of rock fracturing processes, we applied Keilis-Borok’s algorithm M8, originally designed for identifying times of increased probability (TIPS) of occurrence of strong earthquakes (M < 8.0), retrospectively to Koyna earthquakes which occurred in the region after the impoundment of the Shivaji Sagar reservoir in 1962. The algorithm which enables diagnosis of TIPS from the 7th year onwards after the commencement of the earliest available data set showed that the 5.3 magnitude earthquake of 20 September 1980 indeed occurred within a time of increased probability. This result, apart from its potential application to recognizing future TIPS in the region, points to selfsimilarity between the premonitory patterns of natural and induced earthquakes and to scale-invariant nature of their processes. Further, a typical precursory rise in seismicity followed by a relative quiescence was also found to precede all the three larger earthquakes of the sequence.     

应用模式识别定量划分潜在震源区

本文以陕西关中及部分邻区为例,考虑地质构造、地震活动及地球物地场等因素,采用不同的模式识别方法和多种计算方案,以定量判定潜在震源区。其结果表明,模式识别方法有利于地质、地震活动及地球物理场等多种因素综合应用,并能选择和显示判定潜有震源区的主要特征。不同模式识别方法的比较和多种试验方案的综合,则可提高潜在震源区判定的可靠性和稳定性。     

第二代航磁黄沙坪异常的分解及其矿产新空间

本文采用同时具有识別、分解、解释异常三重作用的三元解释法■,在黄沙坪异常负值区有效地提取了由未知的深源磁性体引起的剩余异常。该异常与已知的中、浅源磁性体分处于极为类同的成矿地质背景中。后者与隐伏岩体、铅锌多金属盲矿体之间有着密切的成生联系。这为前者间接找矿提供了有力的依据。定量解释结果中,两者间的磁矩等效关系,论证了已知矿床西侧深部空间里,仍存在找到又一个大型矿床的前景。