MAPPING AND END USER INTERFACE FOR TOPIC MODELS OF NIH GRANTS

2007年秋季，国家土著发展研究所开始审查资助赠款，作为总体战略规划工作的一部分。NINDS咨询理事会的一名成员指导该研究所使用基于网络的技术来分析神经科学学会的约14，000份年会摘要（http：//scimaps.org/maps/neurovis/new/）。该技术使用了一种称为Latent Dirichlet Allocation（潜在狄利克雷分配）的可用主题建模算法来确定单个SfN摘要的主题分布，并使用了一种称为EQUINSITE的模拟退火图形布局算法（后来并入DrL-SAND 2008 - 2936 J：桑迪亚国家实验室）将摘要之间的主题关系映射到谷歌地图应用程序界面中，其中用户可以从二维彩色编码地图中选择摘要集，并通过底层数据库访问关于这些摘要的主题信息。开发这一框架的团队，南加州大学（USC）的Gully Burns，加州欧文大学（UCI）的大卫纽曼和印第安纳州大学（IU）的布鲁斯赫尔（Bruce Herr），同意将其应用于一系列NIH赠款，以测试其对NIH工作人员和校外科学家的潜在效用。随后，该项目扩大到对2007年NIH全部赠款进行建模和绘图，并由此产生了彩色编码地图和主题数据库。这项工作的结果可以在http://scimaps.org/maps/ninds/和http://scimaps.org/maps/nih/2007/上查看。在即将到来的项目期间，该研究所已获得马萨诸塞州大学信息提取和综合实验室（IESL）的服务，以执行NIH赠款的主题建模。基本的赠款数据加上主题模型分析的结果将被传输到Chalklabs，Chalklabs将把它集成到一个界面中，用于主题模型浏览和使用DrL算法进行映射。

In the fall of 2007, NINDS initiated a review of funded grants as part of a general strategic planning effort. The Institute was directed by a member of the NINDS advisory council to a web-based technique for analyzing the ~14,000 Annual Meeting abstracts of the Society for Neuroscience (http://scimaps.org/maps/neurovis/new/). This technique used a publically available topic modeling algorithm known as Latent Dirichlet Allocation to determine the topic distribution of individual SfN abstracts, and used a simulated annealing graphical layout algorithm known as VxINSITE (later incorporated into DrL - SAND2008-2936J: Sandia National Laboratories) to map the topical relationships between abstracts into a Google Maps application interface, in which users can select sets of abstracts from a two-dimensional color-coded map and access topical information regarding these abstracts via an underlying database. The team that developed this framework, Gully Burns at University of Southern California (USC), David Newman at University of California Irvine (UCI), and Bruce Herr at Indiana University (IU), agreed to apply it to a set of NIH grants in order to test its potential utility for NIH staff and extramural scientists. Subsequently the project was expanded to model and map the entire 2007 set of NIH grants, with a resulting color-coded map and topic database. The results of this work can be viewed at http://scimaps.org/maps/ninds/ and http://scimaps.org/maps/nih/2007/. For the upcoming project period, the Institute has enlisted the services of the Information Extraction and Synthesis Laboratory (IESL) at the University of Massachusetts to perform topic modeling of NIH grants. The basic grants data plus the results of the topic model analysis will be transferred to Chalklabs, which will integrate it into an interface for Topic Model Browsing and for mapping using the DrL algorithm.