Results (2)
Search Parameters:
Author/Affiliation: Sint Sint AungTPMTM: Topic Modeling over Papers’ Abstract
Probabilities topic models are active research area in text mining, machine learning, information retrieval, etc. Most of the current statistical topic modeling methods, such as Probabilistic Latent Semantic Analysis (pLSA) and Latent Dirichlet Allocation (LDA). They are used to build models from unstructured text and produce a term-based representation to describe a topic by choosing…
Read MoreDomain Independent Feature Extraction using Rule Based Approach
Sentiment analysis is one of the most popular information extraction tasks both from business and research prospective. From the standpoint of research, sentiment analysis relies on the methods developed for natural language processing and information extraction. One of the key aspects of it is the opinion word lexicon. Product’s feature from online reviews is an…
Read More
