نتایج جستجو برای: topic modeling

تعداد نتایج: 543140  

Journal: :CoRR 2017
Di Jiang Zeyu Chen Rongzhong Lian Siqi Bao Chen Li

Familia is an open-source toolkit for pragmatic topic modeling in industry. Familia abstracts the utilities of topic modeling in industry as two paradigms: semantic representation and semantic matching. Efficient implementations of the two paradigms are made publicly available for the first time. Furthermore, we provide off-the-shelf topic models trained on large-scale industrial corpora, inclu...

Journal: :Journal of Machine Learning Research 2012
Jia Zeng

Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interests and touches on many important applications in text mining, computer vision and computational biology. This paper introduces a topic modeling toolbox (TMBP) based on the belief propagation (BP) algorithms. TMBP toolbox is implemented by MEX C++/Matlab...

Background and aim: Four text mining methods are examined and focused on understanding and identifying their properties and limitations in subject discovery. Methodology: The study is an analytical review of the literature of text mining and topic modeling.  Findings: LSA could be used to classify specific and unique topics in documents that address only a single topic. The other three text min...

Journal: :Journal of the American Medical Informatics Association : JAMIA 2014
Rachel Chasin Anna Rumshisky Özlem Uzuner Peter Szolovits

OBJECTIVE To evaluate state-of-the-art unsupervised methods on the word sense disambiguation (WSD) task in the clinical domain. In particular, to compare graph-based approaches relying on a clinical knowledge base with bottom-up topic-modeling-based approaches. We investigate several enhancements to the topic-modeling techniques that use domain-specific knowledge sources. MATERIALS AND METHOD...

2017
Gerald Conheady Derek Greene

Semi-supervised algorithms have been shown to improve the results of topic modeling when applied to unstructured text corpora. However, sufficient supervision is not always available. This paper proposes a new process, Weak+, suitable for use in semi-supervised topic modeling via matrix factorization, when limited supervision is available. This process uses word embeddings to provide additional...

Journal: :CoRR 2015
Yogesh A. Girdhar Gregory Dudek

Topic modeling of streaming sensor data can be used for high level perception of the environment by a mobile robot. In this paper we compare various Gibbs sampling strategies for topic modeling of streaming spatiotemporal data, such as video captured by a mobile robot. Compared to previous work on online topic modeling, such as o-LDA and incremental LDA, we show that the proposed technique resu...

2015
Ziqiang Cao Sujian Li Yang Liu Wenjie Li Heng Ji

Topic modeling techniques have the benefits of modeling words and documents uniformly under a probabilistic framework. However, they also suffer from the limitations of sensitivity to initialization and unigram topic distribution, which can be remedied by deep learning techniques. To explore the combination of topic modeling and deep learning techniques, we first explain the standard topic mode...

2016
Sergei Koltcov Sergey I. Nikolenko Olessia Koltsova Vladimir Filippov Svetlana Bodrunova

Topic modeling has emerged over the last decade as a powerful tool for analyzing large text corpora, including Web-based usergenerated texts. Topic stability, however, remains a concern: topic models have a very complex optimization landscape with many local maxima, and even different runs of the same model yield very different topics. Aiming to add stability to topic modeling, we propose an ap...

Journal: :CoRR 2013
Pengtao Xie Eric P. Xing

Document clustering and topic modeling are two closely related tasks which can mutually benefit each other. Topic modeling can project documents into a topic space which facilitates effective document clustering. Cluster labels discovered by document clustering can be incorporated into topic models to extract local topics specific to each cluster and global topics shared by all clusters. In thi...

Journal: :CoRR 2017
Efsun Sarioglu Kayi Kabir Yadav James M. Chamberlain Hyeong-Ah Choi

Electronic health records (EHRs) contain important clinical information about patients. Efficient and effective use of this information could supplement or even replace manual chart review as a means of studying and improving the quality and safety of healthcare delivery. However, some of these clinical data are in the form of free text and require pre-processing before use in automated systems...

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