ITR: Unified Graphical Models of Information Extraction and Data Mining with Application to Social Network Analysis

该项目旨在提高我们对以前锁定在非结构化自然语言文本中的信息进行数据挖掘的能力。它专注于开发用于信息提取和数据挖掘的新型统计模型，这些模型具有如此紧密的集成，以至于它们之间的边界消失了——从而产生用于提取和挖掘的强大的统一框架。当前的信息提取方法通过识别文本的相关子序列来填充数据库中的槽，但它们通常没有意识到数据库中出现的模式和规律。当前的数据挖掘方法是从一个已填充的数据库开始的，它们通常不知道数据来自哪里，也不知道其固有的不确定性。结果是两者的准确性都受到影响，对复杂文本源的重要挖掘是无法实现的。该项目使用概率图形模型，在相同的概率货币中进行提取和挖掘决策，并使用通用的推理过程。这样的模型承诺在准确性和能力方面有显著的提高，并且有机会更深入地理解自然语言处理中高层次的、自上而下的模式的作用，以及符号处理中低层次的、自下而上的语言数据的作用。该项目将这项工作基于两个现实世界的应用领域：科学研究和政府信息。通过提供有用的、不断更新的网络资源，通过洞察政府效率和科学思想的流动，以及通过公开数据库、分析和源代码，对这些领域的大规模数据库的提取和挖掘将产生广泛的影响。http://kdl.cs.umass.edu/projects/unified-graphical-models.html

This project aims to improve our ability to data mine information previously locked in unstructured natural language text. It focuses on developing novel statistical models for information extraction and data mining that have such tight integration that the boundaries between them disappear---resulting in a powerful unified framework for extraction and mining. Current information extraction methods populate slots in a database by identifying relevant subsequences of text, but they are usually unaware of the emerging patterns and regularities in the database. Current data mining methods begin from a populated database, and they are often unaware of where the data came from, or its inherent uncertainties. The result is that the accuracy of both suffers, and significant mining of complex text sources is beyond reach. This project uses probabilistic graphical models that make extraction and mining decisions in the same probabilistic currency, with a common inference procedure. Such models promise significant gains in accuracy and capability, as well as an opportunity for deeper understanding of the role of high-level, top-down patterns in natural language processing, and the role of low-level, bottom-up language data in symbolic processing. The project grounds this work in two real-world applications domains: scientific research and government information. The extraction and mining of large-scale databases in these domains will have broad impacts by providing useful, constantly-updated Web resources, by enabling insights into government efficiency and the flow of scientific ideas, and by making databases, analyses and source code publicly available.http://kdl.cs.umass.edu/projects/unified-graphical-models.html