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ICPR
2010
IEEE
13 years 4 months ago
Unsupervised Learning from Linked Documents
Documents in many corpora, such as digital libraries and webpages, contain both content and link information. In a traditional topic model which plays an important role in the uns...
Zhen Guo, Shenghuo Zhu, Yun Chi, Zhongfei Zhang, Y...
ICDIM
2007
IEEE
14 years 2 days ago
Exploiting multi-evidence from multiple user's interests to personalizing information retrieval
The goal of personalization in information retrieval is to tailor the search engine results to the specific goals, preferences and general interests of the users. We propose a no...
Lynda Tamine-Lechani, Mohand Boughanem, Nesrine Ze...
AIRS
2009
Springer
14 years 11 days ago
A Latent Dirichlet Framework for Relevance Modeling
Relevance-based language models operate by estimating the probabilities of observing words in documents relevant (or pseudo relevant) to a topic. However, these models assume that ...
Viet Ha-Thuc, Padmini Srinivasan
NIPS
2004
13 years 7 months ago
A Probabilistic Model for Online Document Clustering with Application to Novelty Detection
In this paper we propose a probabilistic model for online document clustering. We use non-parametric Dirichlet process prior to model the growing number of clusters, and use a pri...
Jian Zhang 0003, Zoubin Ghahramani, Yiming Yang
KDD
2010
ACM
218views Data Mining» more  KDD 2010»
13 years 9 months ago
Online multiscale dynamic topic models
We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
Tomoharu Iwata, Takeshi Yamada, Yasushi Sakurai, N...