EmoSenticSpace: A novel framework for affective common-sense reasoning
نویسندگان
چکیده
منابع مشابه
EmoSenticSpace: A novel framework for affective common-sense reasoning
Emotions play a key role in natural language understanding and sensemaking. Pure machine learning usually fails to recognize and interpret emotions in text. The need for knowledge bases that give access to semantics and sentics (the conceptual and affective information) associated with natural language is growing exponentially in the context of big social data analysis. To this end, this paper ...
متن کاملSentic Activation: A Two-Level Affective Common Sense Reasoning Framework
An important difference between traditional AI systems and human intelligence is our ability to harness common sense knowledge gleaned from a lifetime of learning and experiences to inform our decision making and behavior. This allows humans to adapt easily to novel situations where AI fails catastrophically for lack of situation-specific rules and generalization capabilities. Common sense know...
متن کاملSentic Panalogy: Swapping Affective Common Sense Reasoning Strategies and Foci
An important difference between traditional AI systems and human intelligence is our ability to harness common sense knowledge gleaned from a lifetime of learning and experiences to inform our decision-making and behavior. This allows humans to adapt easily to novel situations where AI fails catastrophically for lack of situation-specific rules and generalization capabilities. In order for mach...
متن کامل280 Common Sense Reasoning
Even with powerful numerical computers, exploring complex dynamical systems requires significant human effort and judgment to prepare simulations and to interpret numerical results. This paper describes one-aspect of a computer program, KAM, that can autonomously prepare numerical simulations, and can automatically generate high-level, qualitative interpretations of the quantitative results. Gi...
متن کاملImplicit Learning of Common Sense for Reasoning
We consider the problem of how enormous databases of “common sense” knowledge can be both learned and utilized in reasoning in a computationally efficient manner. We propose that this is possible if the learning only occurs implicitly, i.e., without generating an explicit representation. We show that it is feasible to invoke such implicitly learned knowledge in essentially all natural tractable...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Knowledge-Based Systems
سال: 2014
ISSN: 0950-7051
DOI: 10.1016/j.knosys.2014.06.011