Results 71 to 80 of about 27,829 (250)
Two knowledge-based methods for High-Performance Sense Distribution Learning [PDF]
Knowing the correct distribution of senses within a corpus can potentially boost the performance of Word Sense Disambiguation (WSD) systems by many points.
Navigli, Roberto, Pasini, Tommaso
core +1 more source
Lexical Chain dan Word Sense Disambiguation Untuk Peringkasan Artikel Berbahasa Indonesia
Text Summarization adalah sebuah proses untuk menghasilkan ringkasan suatu dokumen dengan tidak menghilangkan informasi utama dari artikel. Ada beberapa metode untuk melakukan peringkasan, seperti metode rantai leksikal atau lexical chain yang memiliki ...
Dika Muhammad Fazar+1 more
doaj
Randomly sparsified Richardson iteration: A dimension‐independent sparse linear solver
Abstract Recently, a class of algorithms combining classical fixed‐point iterations with repeated random sparsification of approximate solution vectors has been successfully applied to eigenproblems with matrices as large as 10108×10108$10^{108} \times 10^{108}$. So far, a complete mathematical explanation for this success has proven elusive.
Jonathan Weare, Robert J. Webber
wiley +1 more source
ABSTRACT In China, as the mining depth of coal mines increases, the occurrence conditions of coal seams are becoming increasingly complex, leading to a continuous rise in the risk of rock‐burst. The frequent occurrence of such accidents has caused severe losses to the safe production of coal mines.
Shuheng Zhong, Qi Wang, Haoliang Yin
wiley +1 more source
Word Sense Disambiguation: An Overview [PDF]
AbstractWord sense disambiguation is a subfield of computational linguistics in which computer systems are designed to determine the appropriate meaning of a word as it appears in the linguistic context. This article provides a survey of what has been done in this area: the ways that word meaning can be represented in the computer, the approaches taken
openaire +2 more sources
Analysis and Evaluation of Language Models for Word Sense Disambiguation
Transformer-based language models have taken many fields in NLP by storm. BERT and its derivatives dominate most of the existing evaluation benchmarks, including those for Word Sense Disambiguation (WSD), thanks to their ability in capturing context ...
Daniel Loureiro+3 more
doaj +1 more source
Who gets redeployed? Inventor characteristics and resource redeployment decisions
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
Word Sense Disambiguation with THESSOM [PDF]
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
Word Sense Disambiguation Based on RegNet With Efficient Channel Attention and Dilated Convolution
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
Exploring a Systems Engineering Approach to Modelling Human Communication
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