发帖
雷达卡
摘要翻译：
大多数与单一性有关的工作是作为确定寿命的更大努力的一部分进行的。因此，研究单一性概念并产生专门测量单一性技术的独立研究数量极少。我们提出了一种新的方法，不受时间性的任何影响，它提供了从解析文本中收集语言证据和从谷歌搜索引擎中收集统计证据来测量单一性的专门措施。我们对1005个测试用例的准确性和查全率分别为98.68%和91.82%，准确率为95.42%。
---
英文标题：
《Determining the Unithood of Word Sequences using Mutual Information and
Independence Measure》
---
作者：
Wilson Wong, Wei Liu, Mohammed Bennamoun
---
最新提交年份：
2008
---
分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--
---
英文摘要：
Most works related to unithood were conducted as part of a larger effort for the determination of termhood. Consequently, the number of independent research that study the notion of unithood and produce dedicated techniques for measuring unithood is extremely small. We propose a new approach, independent of any influences of termhood, that provides dedicated measures to gather linguistic evidence from parsed text and statistical evidence from Google search engine for the measurement of unithood. Our evaluations revealed a precision and recall of 98.68% and 91.82% respectively with an accuracy at 95.42% in measuring the unithood of 1005 test cases.
---
PDF链接：
https://arxiv.org/pdf/0810.0156
京公网安备 11010802022788号
