Integrating Natural Language, Knowledge Representation and Reasoning, and Analogical Processing to Learn by Reading
نویسندگان
چکیده
•radically change the economics of building large knowledge bases •provide a platform for cognitive simulations of larger-scale phenomena •Learning Reader learns by reading simplified language texts •Manages syntactic complexity •Unconstrained vocabulary, unlike controlled languages •Learning Reader combines •Natural language processing •A large-scale knowledge base •Deductive reasoning •Analogical processing •Novel aspects •Large scale integration •Memory-based parsing over a large scale knowledge base •Rumination over new knowledge •Automatic axiom extraction for reasoning •Experiments indicate that Learning Reader successfully accumulates and applies new knowledge from simplified texts Overview Integrating Natural Language, Knowledge Representation and Reasoning, and Analogical Processing to Learn by Reading
منابع مشابه
Generation Learning by Reading System
Learning by reading is an important scientific problem because it requires modeling a wide range of human abilities. It also could break the knowledge engineering bottleneck, enabling the bootstrapping of intelligent systems via interaction with people using natural language. This paper outlines our progress on creating a 2 generation learning by reading system, focusing on three main areas: Mu...
متن کاملProcedural Meaning Representation by Connotative Dependency Structures an Empirical Approach to Word Semantics for Analogical Inferencing
Natural language understanding systems make use of language and/or world knowledge bases. One of the salient problems of meaning representation and knowledge structure is the modelling of its acquisition and modiication from natural language processing. Based upon the statistical analysis of discourse, a formal representation of vague word meanings is derived which constitutes the lexical struc...
متن کاملUsing analogy to acquire commonsense knowledge from human Contributors
The goal of the work reported here is to capture the commonsense knowledge of non-expert human contributors. Achieving this goal will enable more intelligent human-computer interfaces and pave the way for computers to reason about our world. In the domain of natural language processing, it will provide the world knowledge much needed for semantic processing of natural language. To acquire knowl...
متن کاملExplanation Generation for a Math Word Problem Solver
Background Machine Reading (MR) aims to make the knowledge contained in the text available in forms that machines can use them for automated processing. That is, machines will learn to read from a few examples and they will read to learn what they need in order to answer questions or perform some reasoning task [1]. Since a domain-independent MR system is difficult to build, the Math Word Probl...
متن کاملIntroduction to ROSS
Representation is a cross-discipline topic that includes knowledge representation from the field of artificial intelligence, meaning representation from the field of natural language understanding, and structured information from information processing. The field of logic is replete with methods for representation and reasoning. In the areas of AI knowledge representation and reasoning, leading...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007