This paper presents a novel approach for exploiting the global context for the task of word sense disambiguation (WSD). This is done by using topic features constructed using the ...
In this paper we propose a domainindependent text segmentation method, which consists of three components. Latent Dirichlet allocation (LDA) is employed to compute words semantic ...
Abstract. Probabilistic models with hidden variables such as probabilistic Latent Semantic Analysis (pLSA) and Latent Dirichlet Allocation (LDA) have recently become popular for so...
In this paper, we focus our attention on the problem of computing the ratio of two numbers, both of which are the summations of the private numbers distributed in different parties...
One of the important approaches for Knowledge discovery and Data mining is to estimate unobserved variables because latent variables can indicate hidden and specific properties o...
Abstract. This paper presents PLDA, our parallel implementation of Latent Dirichlet Allocation on MPI and MapReduce. PLDA smooths out storage and computation bottlenecks and provid...
Yi Wang, Hongjie Bai, Matt Stanton, Wen-Yen Chen, ...
Abstract. As a low-cost ressource that is up-to-date, Wikipedia recently gains attention as a means to provide cross-language brigding for information retrieval. Contradictory to a...
Latent Dirichlet Allocation (LDA) is a fully generative approach to language modelling which overcomes the inconsistent generative semantics of Probabilistic Latent Semantic Index...
Abstract. This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-...
Search algorithms incorporating some form of topic model have a long history in information retrieval. For example, cluster-based retrieval has been studied since the 60s and has ...