ConceptNet is a knowledge representation project, providing a large semantic graph that describes general human knowledge and how it is expressed in natural language. This paper presents the latest iteration, ConceptNet 5, including its fundamental design decisions, ways to use it, and evaluations of its coverage and accuracy.

This paper introduces a new methodology of revising general KBs in DL-Lite. Two specific revision operators are defined, their properties are investigated and algorithms for computing revisions are developed.

In this paper we present an unsupervised approach to relational information extraction. Our model partitions tuples representing an observed syntactic relationship between two named entities (e.g., “X was born in Y” and “X is from Y”) into clusters corresponding to underlying semantic relation types (e.g., BornIn, Located). Our approach incorporates general domain knowledge which we encode as F...

We analyze how the cost of transfering specific knowledge encourages the decentralization of decision rights and how this decentralization generates the rights assignment and control problems. Ignoring agency problems, assigning decisions rights to individuals who have the decision-relevant knowledge and abilities increases efficiency. Self interest on the part of individual decisionmakers, how...

Knowledge Visualizer (KV) uses a General Logic Diagram (GLD) to display examples and/or various forms of knowledge learned from them in a planar model of a multi-dimensional discrete space. Knowledge can be in different forms, for example, decision rules, decision trees, logical expressions, clusters, classifiers, and neural nets with discrete input variables. KV is implemented as a module of t...

Knowledge is not a simple concept to define, and although many definitions have been given of it, only a few describe the concept with enough detail to grasp it in practical terms; knowledge is sometimes seen as a thing out in the real word waiting to be uncovered and taken in by the receptive mind; however, knowledge is not a thing to be encountered and taken in, no knowledge can be found in a...

We present a reinforcement learning game player that can interact with a General Game Playing system and transfer knowledge learned in one game to expedite learning in many other games. We use the technique of value-function transfer where general features are extracted from the state space of a previous game and matched with the completely different state space of a new game. To capture the un...

In data exchange, one is typically given a source database instance and a mapping between a source schema and a target schema. The goal then is to materialize a target database instance that corresponds to the source instance and the mapping. In this setting source data is explicitly given, that is, every fact that is true in it is explicitly mentioned in the source database instance. Knowledge...

This project was concerned with the clinical knowledge reported by general practitioners in relation to the diagnosis and management of seven common clinical conditions: acute otitis media, jaundice, iron-deficiency anaemia, transient cerebral vascular insufficiency, infectious mononucleosis, pulmonary infarction, and carcinoma of the prostate. Postal questionnaires were sent to three groups of...

In this paper, based on the work in , we further give a general model for acquiring knowledge, which first focuses on the research of how and when things involved in problems are made then describes the goals, the energy and the time to give an optimum model to decide how many related things are supposed to be involved in. Finally, we acquire knowledge from this model in which there are the att...