Latent Dirichlet Allocation-Based Topic Mining Analysis of Educational Scientific Research Projects Based on 2360 NSF Education Projects

Topic Models - Latent Dirichlet Allocation

Research on Image Semantic Information Mining Based On Latent Dirichlet Allocation Model

Focusing on the issues of lacking of semantic description on image identification and methods of mapping from low-level semantics to high-level semantics, this paper describes the experiments of identification of image semantic information by using LDA model, which can achieve the mapping from image visual feature to high-level semantics, and experiments on the data sets of Corel 5k and Corel 3...

Similarity Measures Based on Latent Dirichlet Allocation

We present in this paper the results of our investigation on semantic similarity measures at wordand sentence-level based on two fully-automated approaches to deriving meaning from large corpora: Latent Dirichlet Allocation, a probabilistic approach, and Latent Semantic Analysis, an algebraic approach. The focus is on similarity measures based on Latent Dirichlet Allocation, due to its novelty ...

Automatic keyword extraction using Latent Dirichlet Allocation topic modeling: Similarity with golden standard and users' evaluation

Purpose: This study investigates the automatic keyword extraction from the table of contents of Persian e-books in the field of science using LDA topic modeling, evaluating their similarity with golden standard, and users' viewpoints of the model keywords. Methodology: This is a mixed text-mining research in which LDA topic modeling is used to extract keywords from the table of contents of sci...

Decentralized Topic Modelling with Latent Dirichlet Allocation

Privacy preserving networks can be modelled as decentralized networks (e.g., sensors, connected objects, smartphones), where communication between nodes of the network is not controlled by a master or central node. For this type of networks, the main issue is to gather/learn global information on the network (e.g., by optimizing a global cost function) while keeping the (sensitive) information ...