Results 101 to 110 of about 83,244 (255)
Word Sense Disambiguation Focusing on POS Tag Disambiguation in Persian:
International Journal of Information Science and Management, 2019 The present study deals with ambiguity at word level focusing on homographs. In different languages, homographs may cause ambiguity in text processing. In Persian, the number of homographs is high due to its orthographic structure as well as its complex ...
Elham Alayiaboozar +2 more
doaj
Improving Word Sense Disambiguation with Translations
Conference on Empirical Methods in Natural Language Processing, 2020 It has been conjectured that multilingual information can help monolingual word sense disambiguation (WSD). However, existing WSD systems rarely consider multilingual information, and no effective method has been proposed for improving WSD by generating ...
Yixing Luan +3 more
semanticscholar +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 concept-based adaptive approach to word sense disambiguation [PDF]
, 1998 Jen Nan Chen, Jason S. Chang
openalex +2 more sources
Toward Universal Word Sense Disambiguation Using Deep Neural Networks
IEEE Access, 2019 Traditionally, approaches based on neural networks to solve the problem of disambiguation of the meaning of words (WSD) use a set of classifiers at the end, which results in a specialization in a single set of words-those for which they were trained ...
Hiram Calvo +3 more
doaj +1 more source
Journal of Language ModellingWe develop a three-part approach to Verb Sense Disambiguation (VSD) in German. After considering a set of lexical resources and corpora, we arrive at a statistically motivated selection of a subset of verbs and their senses from GermaNet.
Dominik Mattern +3 more
doaj +2 more sources
Neural Sequence Learning Models for Word Sense Disambiguation
Conference on Empirical Methods in Natural Language Processing, 2017 Word Sense Disambiguation models exist in many flavors. Even though supervised ones tend to perform best in terms of accuracy, they often lose ground to more flexible knowledge-based solutions, which do not require training by a word expert for every ...
Alessandro Raganato +2 more
semanticscholar +1 more source
An Optimized Lesk-Based Algorithm for Word Sense Disambiguation
Open Computer Science, 2016 Computational complexity is a characteristic of almost all Lesk-based algorithms for word sense disambiguation (WSD). In this paper, we address this issue by developing a simple and optimized variant of the algorithm using topic composition in documents ...
Ayetiran Eniafe Festus, Agbele Kehinde
doaj +1 more source
Knowledge Sources for Word Sense Disambiguation
, 2001 Two kinds of systems have been defined during the long history of WSD: principled systems that define which knowledge types are useful for WSD, and robust systems that use the information sources at hand, such as, dictionaries, light-weight ontologies or hand-tagged corpora.
David Martinez, Eneko Agirre
openaire +2 more sources
Sometimes less is more : Romanian word sense disambiguation revisited [PDF]
, 2007 Recent approaches to Word Sense Disambiguation (WSD) generally fall into two classes: (1) information-intensive approaches and (2) information-poor approaches.
Dinu, Georgiana, Kübler, Sandra
core