… on the research problem which was that word ambiguity in … used in various fields like
machine learning and so on. But in … to WSD in the biomedical domain. Personalized PageRank …

… is said to be a long last Computational Linguistic Problem. … biomedical documents by training
the machine learning model … Machine learning-based WSD. A lot of work has been done to …

… problem is addressed in this chapter, as bio-med domain, … cell line”, in this biomedical entity,
multiple words are present, but still … For lack of data and entity misclassification problem, this …

… Going back to the biomedical domain, in the sentence "Recently… on this problem and proposes
an evaluation framework to … Here, we will focus on machine learning methods using graph …

… for humans, machines face tremendous challenges in … With the introduction of supervised
machine learning in the 1990s, … : All-words word sense disambiguation on a specific domain. …

… viewed as a word sense disambiguation (WSD) problem (7), … , especially in the biomedical
domain, where a variety of rule-… to train a deep learning model for disambiguation of global …

… class is a well-known problem in Machine Learning. Different techniques have been …
when we consider disambiguating texts that lie in a specific domain where the predominant …

… open issues and challenges in the domain of the biomedical … the review paper by identifying
current challenges and open … According to the medical word sense disambiguation, there …

… One issue with word sense disambiguation is defining … WSD has probably been subjected
to every machine learning … outcomes in domain-specific word sense disambiguation as well. …

… care and biomedicine of clinical text … domain is generated based on Word sense
disambiguation concept in the NLP. Syntactic or semantic ambiguity, Lexical ambiguity are the …