Results 111 to 120 of about 83,914 (327)
Error driven word sense disambiguation [PDF]
Proceedings of the 36th annual meeting on Association for Computational Linguistics -, 1998 In this paper we describe a method for performing word sense disambiguation (WSD). The method relies on unsupervised learning and exploits functional relations among words as produced by a shallow parser. By exploiting an error driven rule learning algorithm (Brill 1997), the system is able to produce rules for WSD, which can be optionally edited by ...
Luca Dini +2 more
openaire +3 more sources
Who gets redeployed? Inventor characteristics and resource redeployment decisions
Strategic Management Journal, EarlyView.Abstract Research Summary While the literature highlights the benefits of internally redeploying resources, there is less empirical guidance on which resources are most likely to be redeployed. We examine the relationship between inventor characteristics and redeployment decisions, motivated by the tension between costs and benefits of keeping a ...
Kyungsoo Kim, Isin Guler, Samina Karim
wiley +1 more source
Exploring a Systems Engineering Approach to Modelling Human Communication
Systems Research and Behavioral Science, EarlyView.ABSTRACT Communication is a crucial process for any successful purposeful human activity system as it mediates the information‐based relationships between a system's elements and parts, purpose(s) and boundaries. Human communication is more than just a process; it is a subsystem that interacts with other human activity systems, parts, elements and ...
Ryan Hekker +2 more
wiley +1 more source
Systems Engineering, EarlyView.ABSTRACT Multi‐purpose large language models (LLMs), a subset of generative artificial intelligence (AI), have recently made significant progress. While expectations for LLMs to assist systems engineering (SE) tasks are paramount; the interdisciplinary and complex nature of systems, along with the need to synthesize deep‐domain knowledge and ...
Taylan G. Topcu +3 more
wiley +1 more source
Word Sense Disambiguation Based on RegNet With Efficient Channel Attention and Dilated Convolution
IEEE Access, 2023 Word sense disambiguation (WSD) is one of key problems in field of natural language processing. Ambiguous word often has different meanings in different contexts.
Chun-Xiang Zhang +2 more
doaj +1 more source
Word Sense Disambiguation with THESSOM [PDF]
, 2003 Word sense disambiguation automatically determines the appropriate senses of a word in context. We have previously shown that self-organized document maps have properties similar to a large-scale semantic structure that is useful for word sense ...
Linden, Krister
core
A Synset Relation-enhanced Framework with a Try-again Mechanism for Word Sense Disambiguation
Conference on Empirical Methods in Natural Language Processing, 2020 Contextual embeddings are proved to be overwhelmingly effective to the task of Word Sense Disambiguation (WSD) compared with other sense representation techniques. However, these embeddings fail to embed sense knowledge in semantic networks.
Ming Wang, Yinglin Wang
semanticscholar +1 more source
Journal of Research in Science Teaching, EarlyView.ABSTRACT Promoting argumentation based on evidence allows students to give meaning to the phenomena observed, enabling the construction of knowledge. Children's argumentative discourse can be activated by appropriate instruction, but there is little information on argumentation at early ages and there is a need for the teacher to understand how to ...
Lidia Caño, Josu Sanz
wiley +1 more source
Try to Substitute: An Unsupervised Chinese Word Sense Disambiguation Method Based on HowNet
International Conference on Computational Linguistics, 2020 Word sense disambiguation (WSD) is a fundamental natural language processing task. Unsupervised knowledge-based WSD only relies on a lexical knowledge base as the sense inventory and has wider practical use than supervised WSD that requires a mass of ...
Bairu Hou +5 more
semanticscholar +1 more source
TESOL Quarterly, EarlyView.Abstract Recent research on learner factors in task‐based language teaching (TBLT) has demonstrated positive effects for treatments that draw on learners' personal experiences. However, the specific processes responsible for these effects are not well understood.
Taghreed Qahl, Craig Lambert
wiley +1 more source