A Logical Model for Supporting Social Commonsense Knowledge Acquisition
Zhenzhen Gu, Cungen Cao, Ya Wang, Yuefei Sui

TL;DR
This paper proposes a formal logical model for representing social commonsense knowledge (SCK), defining its basic types and structures to facilitate large-scale acquisition for intelligent systems.
Contribution
It introduces a formal first-order logic framework for modeling three fundamental types of social commonsense knowledge and their intrinsic information structures.
Findings
Formalizes interrelationships among social contexts, roles, and players.
Provides a four-level structure for intrinsic social context information.
Describes methods to extract intrinsic information from contexts and roles.
Abstract
To make machine exhibit human-like abilities in the domains like robotics and conversation, social commonsense knowledge (SCK), i.e., common sense about social contexts and social roles, is absolutely necessarily. Therefor, our ultimate goal is to acquire large-scale SCK to support much more intelligent applications. Before that, we need to know clearly what is SCK and how to represent it, since automatic information processing requires data and knowledge are organized in structured and semantically related ways. For this reason, in this paper, we identify and formalize three basic types of SCK based on first-order theory. Firstly, we identify and formalize the interrelationships, such as having-role and having-social_relation, among social contexts, roles and players from the perspective of considering both contexts and roles as first-order citizens and not generating role instances.…
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Taxonomy
TopicsSemantic Web and Ontologies · Logic, Reasoning, and Knowledge · Multi-Agent Systems and Negotiation
