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EMNLP
2007
15 years 1 months ago
Bayesian Document Generative Model with Explicit Multiple Topics
In this paper, we proposed a novel probabilistic generative model to deal with explicit multiple-topic documents: Parametric Dirichlet Mixture Model(PDMM). PDMM is an expansion of...
Issei Sato, Hiroshi Nakagawa
WEBI
2009
Springer
15 years 6 months ago
Social Semantics and Its Evaluation by Means of Semantic Relatedness and Open Topic Models
—This paper presents an approach using social semantics for the task of topic labelling by means of Open Topic Models. Our approach utilizes a social ontology to create an alignm...
Ulli Waltinger, Alexander Mehler
PR
2007
106views more  PR 2007»
14 years 11 months ago
Extraction and segmentation of tables from Chinese ink documents based on a matrix model
This paper presents an approach for extracting and segmenting tables from Chinese ink documents based on a matrix model. An ink document is first modeled as a matrix containing i...
Xi-Wen Zhang, Michael R. Lyu, Guo-zhong Dai
EMNLP
2008
15 years 1 months ago
HTM: A Topic Model for Hypertexts
Previously topic models such as PLSI (Probabilistic Latent Semantic Indexing) and LDA (Latent Dirichlet Allocation) were developed for modeling the contents of plain texts. Recent...
Congkai Sun, Bin Gao, Zhenfu Cao, Hang Li
UAI
2008
15 years 1 months ago
Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression
Although fully generative models have been successfully used to model the contents of text documents, they are often awkward to apply to combinations of text data and document met...
David M. Mimno, Andrew McCallum