Knowledge representation and reasoning based on entity and relation propagation diagram/tree

No abstract is available for this paper.

• Publication year

  2006

• Venue

  Intelligent Data Analysis

• Publication date

  2006-01-01

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.3233/IDA-2006-10106
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Reasoning Algorithm in Multi-Value Causality Diagram

  2003cited by this paper
• Probabilistic Reasoning for Entity & Relation Recognition

  2002influential reference
• Relational Learning via Propositional Algorithms: An Information Extraction Case Study

  2001cited by this paper
• Overview of the TREC-9 Question Answering Track

  2000cited by this paper
• Machine Learning for Information Extraction in Informal Domains

  2000cited by this paper
• Loopy Belief Propagation for Approximate Inference: An Empirical Study

  1999cited by this paper
• Relational Learning of Pattern-Match Rules for Information Extraction

  1999cited by this paper
• Deep Read: A Reading Comprehension System

  1999cited by this paper
• Learning to Resolve Natural Language Ambiguities: A Unified Approach

  1998cited by this paper
• Parsing By Chunks

  1991cited by this paper
• Principle-Based Parsing: Computation and Psycholinguistics

  1991cited by this paper
• Probabilistic reasoning in intelligent systems - networks of plausible inference

  1989cited by this paper

• Integrate Metadata by Semantic Recommendation: A Psychology Inspired Method

  2015cites this paper
• Dynamic Adaptive Fuzzy Petri Nets for Knowledge Representation and Reasoning

  2013cites this paper
• A Method of Recognizing Entity and Relation

  2005cites this paper