A generalized topic modeling approach for automatic document annotation

[1]  Conrad S. Tucker,et al.  Quantifying Product Favorability and Extracting Notable Product Features Using Large Scale Social Media Data , 2015, J. Comput. Inf. Sci. Eng..

[2]  Conrad S. Tucker,et al.  Automated Discovery of Lead Users and Latent Product Features by Mining Large Scale Social Media Networks , 2015 .

[3]  Conrad S. Tucker,et al.  Discovering Next Generation Product Innovations by Identifying Lead User Preferences Expressed Through Large Scale Social Media Data , 2014 .

[4]  Marcel Salathé,et al.  An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages , 2014, J. Biomed. Informatics.

[5]  Marcel Salathé,et al.  Discovering health-related knowledge in social media using ensembles of heterogeneous features , 2013, CIKM.

[6]  Conrad S. Tucker Fad or Here to Stay: Predicting Product Market Adoption and Longevity Using Large Scale, Social Media Data DETC2013-12661 , 2013 .

[7]  C. Lee Giles,et al.  Automatic tag recommendation for metadata annotation using probabilistic topic modeling , 2013, JCDL '13.

[8]  Wenyi Huang,et al.  Recommending citations: translating papers into references , 2012, CIKM.

[9]  M. de Rijke,et al.  Linking Archives Using Document Enrichment and Term Selection , 2011, TPDL.

[10]  Zhiyuan Liu,et al.  A Simple Word Trigger Method for Social Tag Suggestion , 2011, EMNLP.

[11]  Zhiyuan Liu,et al.  Automatic Keyphrase Extraction via Topic Decomposition , 2010, EMNLP.

[12]  Yasushi Sakurai,et al.  Online multiscale dynamic topic models , 2010, KDD.

[13]  Prasenjit Mitra,et al.  Utilizing Context in Generative Bayesian Models for Linked Corpus , 2010, AAAI.

[14]  Michael R. Lyu,et al.  UserRec: A User Recommendation Framework in Social Tagging Systems , 2010, AAAI.

[15]  Timothy Baldwin,et al.  Automatic Evaluation of Topic Coherence , 2010, NAACL.

[16]  Ralf Krestel,et al.  Latent dirichlet allocation for tag recommendation , 2009, RecSys '09.

[17]  Yee Whye Teh,et al.  On Smoothing and Inference for Topic Models , 2009, UAI.

[18]  Nenghai Yu,et al.  WWW 2009 MADRID! Track: Rich Media / Session: Tagging and Clustering Learning to , 2022 .

[19]  Daniel Barbará,et al.  On-line LDA: Adaptive Topic Models for Mining Text Streams with Applications to Topic Detection and Tracking , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[20]  Yang Song,et al.  Real-time automatic tag recommendation , 2008, SIGIR '08.

[21]  Hector Garcia-Molina,et al.  Social tag prediction , 2008, SIGIR '08.

[22]  Hinrich Schütze,et al.  Introduction to information retrieval , 2008 .

[23]  Dominic Widdows,et al.  Semantic Vectors: a Scalable Open Source Package and Online Technology Management Application , 2008, LREC.

[24]  Max Welling,et al.  Distributed Inference for Latent Dirichlet Allocation , 2007, NIPS.

[25]  Padhraic Smyth,et al.  Subject metadata enrichment using statistical topic models , 2007, JCDL '07.

[26]  Thomas L. Griffiths,et al.  Probabilistic Topic Models , 2007 .

[27]  Ian H. Witten,et al.  Thesaurus based automatic keyphrase indexing , 2006, Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '06).

[28]  Gilad Mishne,et al.  AutoTag: a collaborative approach to automated tag assignment for weblog posts , 2006, WWW '06.

[29]  Sanjay Ghemawat,et al.  MapReduce: simplified data processing on large clusters , 2008, CACM.

[30]  Ellen M. Voorhees,et al.  Retrieval evaluation with incomplete information , 2004, SIGIR '04.

[31]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[32]  Carl Gutwin,et al.  KEA: practical automatic keyphrase extraction , 1999, DL '99.

[33]  Richard A. Harshman,et al.  Indexing by Latent Semantic Analysis , 1990, J. Am. Soc. Inf. Sci..

[34]  Jeffery S. Horsburgh,et al.  ONEMercury: Towards Automatic Annotation of Environmental Science Metadata , 2012, LISC@ISWC.

[35]  John Kunze,et al.  DataONE: Data Observation Network for Earth - Preserving Data and Enabling Innovation in the Biological and Environmental Sciences , 2011, D Lib Mag..

[36]  Thomas Hofmann,et al.  Unsupervised Learning by Probabilistic Latent Semantic Analysis , 2004, Machine Learning.

[37]  Ellen M. Voorhees,et al.  The TREC-8 Question Answering Track Report , 1999, TREC.