Topic modeling for large-scale text data

被引：7

作者：

Li, Xi-ming ^{[1
,2
]}

Ouyang, Ji-hong ^{[1
,2
]}

Lu, You ^{[1
,2
]}

机构：

[1] Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China

[2] Jilin Univ, MOE Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China

来源：

FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING | 2015年 / 16卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Latent Dirichlet allocation (LDA); Topic modeling; Online learning; Moving average;

D O I：

10.1631/FITEE.1400352

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper develops a novel online algorithm, namely moving average stochastic variational inference (MASVI), which applies the results obtained by previous iterations to smooth out noisy natural gradients. We analyze the convergence property of the proposed algorithm and conduct a set of experiments on two large-scale collections that contain millions of documents. Experimental results indicate that in contrast to algorithms named 'stochastic variational inference' and 'SGRLD', our algorithm achieves a faster convergence rate and better performance.

引用

页码：457 / 465

页数：9

共 50 条

[1] Topic modeling for large-scale text data
Xi-ming Li
Ji-hong Ouyang
You Lu
Frontiers of Information Technology & Electronic Engineering, 2015, 16 : 457 - 465
[2] A Large-scale Text Analysis with Word Embeddings and Topic Modeling
Choi, Won-Joon
Kim, Euhee
JOURNAL OF COGNITIVE SCIENCE, 2019, 20 (01) : 147 - 187
[3] Topic Modeling of Large Scale Social Text
Wang, Jia-wen
Yang, Qun
2ND INTERNATIONAL CONFERENCE ON COMMUNICATIONS, INFORMATION MANAGEMENT AND NETWORK SECURITY (CIMNS 2017), 2017, : 237 - 242
[4] Topic Modeling Techniques for Text Mining over a Large-Scale Scientific and Biomedical Text Corpus
Avasthi S.
Chauhan R.
Acharjya D.P.
International Journal of Ambient Computing and Intelligence, 2022, 13 (01)
[5] Empath: Understanding Topic Signals in Large-Scale Text
Fast, Ethan
Chen, Binbin
Bernstein, Michael S.
34TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2016, 2016, : 4647 - 4657
[6] A Distributed Topic Model for Large-Scale Streaming Text
Li, Yicong
Feng, Dawei
Lu, Menglong
Li, Dongsheng
KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT, KSEM 2019, PT II, 2019, 11776 : 37 - 48
[7] LDA*: A Robust and Large-scale Topic Modeling System
Yu, Lele
Zhang, Ce
Shao, Yingxia
Cui, Bin
PROCEEDINGS OF THE VLDB ENDOWMENT, 2017, 10 (11): : 1406 - 1417
[8] Large-scale Analysis of Free-Text Data for Mental Health Surveillance with Topic Modelling
Gu, Yang
Leroy, Gondy
AMCIS 2020 PROCEEDINGS, 2020,
[9] Large-Scale High-Precision Topic Modeling on Twitter
Yang, Shuang
Kolcz, Alek
Schlaikjer, Andy
Gupta, Pankaj
PROCEEDINGS OF THE 20TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (KDD'14), 2014, : 1907 - 1916
[10] Topic modeling and improvement of image representation for large-scale image retrieval
Nguyen Anh Tu
Dong-Luong Dinh
Rasel, Mostofa Kamal
Lee, Young-Koo
INFORMATION SCIENCES, 2016, 366 : 99 - 120

← 1 2 3 4 5 →