Text Simplification using Word Sense Disambiguation Using Knowledge-Based Approach
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Updated
Aug 14, 2017 - Python
Text Simplification using Word Sense Disambiguation Using Knowledge-Based Approach
Slides for tutorials of Statistical Natural Language Processing (SS 2021), Universität des Saarlandes.
This is the implementation of SIGIR - 2005 paper on Iterative translation disambiguation for cross-language information retrieval
Five mini-projects done for the course of Natural Language Technologies held at the Computer Science departement of the University of Turin.
University of Washington, Masters of Computational Linguistics - LING 571 - Deep Processing Techniques for NLP
An out-of-the-box, corpus-agnostic query expansion tool for lexical retrieval systems.
Evaluation (and some implementations/adaptations) of WSD systems for Finnish
Word2Vec Tensorflow implementation with word sense disambiguation.
Implementing Multilingual WSD using [Normal, Atten]BiLSTM, Seq2Seq[Atten], Multitask WSD
Word Sense Annotation on Toloka for RUSSE 2018 WSI&D Task.
Rule-based and statistical methods for creating computer programs that analyze, generate, and understand human language
Neural Word Sense Disambiguation, replicating "Neural Sequence Learning Models for Word Sense Disambiguation", Alessandro Raganato, Claudio Delli Bovi and Roberto Navigli, EMNLP 2017
NLP related problem statements & solutions like NER, WSD & Word Correction according to domain
This repository depicts our attempt to solve the long standing problem of word sense disambiguation in NLP using novel methods like generation of context vectors and sense embeddings.
FaceDetection, ScalingPictures, WordSenseDisambiguation
Word Sense Induction and Disambiguation with Co-occurrences
Sense Tagged Instances For Finnish
Context-Aware Semantic Similarity Measurement for Unsupervised Word Sense Disambiguation
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