III: Small: Collaborative Research: Keyphrase Extraction in Document Networks

III：小：协作研究：文档网络中的关键词提取

• 批准号: 1813571
• 负责人: Cornelia Caragea
• 金额: $ 5.5万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-26 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1813571&HistoricalAwards=false
• 关键词: III; Small; Collaborative; Research; Keyphrase

Keyphrases for a document concisely describe the document using a small set of phrases (i.e., sequences of contiguous words in a document). For example, the keyphrases "social networks" and "interest targeting" quickly provide us with a high-level topic description (i.e., a summary) of a document focused on targeting interest for recommending services such as products and news to users, in the context of social networks. Given today's very large collections of documents, these keyphrases are extremely important not only for summarizing a document, but also for the search and retrieval of relevant information. However, keyphrases are not always available directly. Instead, they need to be gleaned from the many details in documents. This project addresses the problem of automatic keyphrase extraction from research papers, which are enablers of the sharing and dissemination of scientific discoveries. The goal of the project is to explore accurate approaches that automatically discover and extract keyphrases in documents, using document networks, which will help users handle and digest more information in less time during these "big data" times. Educationally, this research will involve training of both graduate and undergraduate students in the active area of research of keyphrase extraction, which has high impact in many real-world applications such as online advertising, document categorization, recommendation, and summarization, Web search and discovery, and topic tracking in newswire. Although much research to date has been done on automatic keyphrase extraction, no previous approaches have captured the impact of documents on one another via the citation relation that connects documents in a network. This project will investigate models that take into consideration the linkage between citing and cited documents in a document network and will explore various qualitative and quantitative aspects of the question: "What are the key phrases or concepts in a document?" Scalable iterative algorithms will be designed and developed that capture different aspects of documents (e.g., topics or concepts), as well as the impact of one document on another (e.g., influence or topic evolution) in a document network. The results of this research will have a direct pipeline to the CiteSeerX digital library (http://citeseerx.ist.psu.edu). The software, tools, and benchmark datasets developed during the course of this project will be broadly disseminated via the project website (http://people.cs.ksu.edu/~ccaragea/keyphrases.html). All findings will be shared to the research community through publications in academic journals and presented in Information Retrieval, Text Mining and Natural Language Processing conferences.

文档的钥匙拼图使用一小部分短语（即文档中连续单词的序列）简单地描述文档。例如，键形的“社交网络”和“兴趣定位”迅速为我们提供了一份文档的高级主题描述（即摘要），该文档着重于在社交网络的背景下针对向用户推荐的服务（例如产品和新闻）的兴趣。鉴于当今的大量文档集合，这些钥匙纸不仅对于总结文档，而且对于搜索和检索相关信息非常重要。但是，键形并不总是直接可用。相反，他们需要从文档中的许多细节中收集到它们。该项目解决了从研究论文中提取自动键形的问题，这些问题是分享和传播科学发现的推动者。该项目的目标是探索使用文档网络自动发现和提取文档中的键形短语的准确方法，这将帮助用户在这些“大数据”时间的时间内更少的时间处理和消化更多信息。在教育上，这项研究将涉及培训研究生和本科生在Keyphrase提取研究的积极领域，该领域在许多真实世界的应用程序中具有很大的影响，例如在线广告，文档分类，建议，建议以及摘要，网络搜索和发现，以及在Newswire的主题跟踪。 尽管迄今为止已经对自动键形提取进行了大量研究，但以前的方法还没有通过连接网络中文档的引文关系捕获了文档对彼此的影响。该项目将调查考虑文档网络中引用和引用文档之间的联系的模型，并将探讨该问题的各种定性和定量方面：“文档中的关键短语或概念是什么？”将设计和开发可扩展的迭代算法，以捕获文档的不同方面（例如主题或概念），以及一个文档对文档网络中另一个文档（例如影响或主题进化）的影响。这项研究的结果将直接提供到Citeseerx数字图书馆（http://citeseerx.ist.ist.psu.edu）。在此项目过程中开发的软件，工具和基准数据集将通过项目网站（http://people.cs.ksu.edu/~ccaragea/keyphrases.html）广泛传播。所有发现将通过学术期刊的出版物与研究社区共享，并在信息检索，文本挖掘和自然语言处理会议中介绍。