Nonparametric topic modeling using chinese restaurant franchise with buddy customers
Refereed conference paper presented and published in conference proceedings


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摘要Many popular latent topic models for text documents generally make two assumptions. The first assumption relates to a finitedimensional parameter space. The second assumption is the bag-of-words assumption, restricting such models to capture the interdependence between the words. While existing nonparametric admixture models relax the first assumption, they still impose the second assumption mentioned above about bag-of-words representation. We investigate a nonparametric admixture model by relaxing both assumptions in one unified model. One challenge is that the state-of-the-art posterior inference cannot be applied directly. To tackle this problem, we propose a new metaphor in Bayesian nonparametrics known as the “Chinese Restaurant Franchise with Buddy Customers”. We conduct experiments on different datasets, and show an improvement over existing comparative models.
著者Jameel S., Lam W., Bing L.
會議名稱37th European Conference on Information Retrieval Research, ECIR 2015
會議開始日29.03.2015
會議完結日02.04.2015
會議地點Vienna,
會議國家/地區奧地利
詳細描述organized by -,
出版年份2015
月份1
日期1
卷號9022
出版社Springer Verlag
出版地Germany
頁次648 - 659
國際標準書號9783319163536
國際標準期刊號1611-3349
語言英式英語

上次更新時間 2020-05-09 於 02:28