PPT-Hetero-Labeled LDA: A partially supervised topic model with heterogeneous label information

Author : sophia2 | Published Date : 2022-06-28

Dongyeop Kang 1 Youngja Park 2 Suresh Chari 2 1 IT Convergence Laboratory KAIST InstituteKorea 2 IBM TJ Watson Research Center NY USA

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Hetero-Labeled LDA: A partially supervised topic model with heterogeneous label information: Transcript

Dongyeop Kang 1 Youngja Park 2 Suresh Chari 2 1 IT Convergence Laboratory KAIST InstituteKorea 2 IBM TJ Watson Research Center NY USA. Yizhou. Sun, Rick Barber, Manish Gupta, . Charu. . C. . Aggarwal. , . Jiawei. Han. 1. Content. Background and motivation. Problem definition. PathPredict. : meta path-based . relationship prediction . Chenghua. Lin . & . Yulan. He. CIKM09. Main Idea. This . paper . proposes . a novel probabilistic modeling framework based on . Latent . Dirichlet. Allocation (LDA), called joint sentiment/. Source: “Topic models”, David . Blei. , MLSS ‘09. Topic modeling - Motivation. Discover topics from a corpus . Model connections between topics . Model the evolution of topics over time . Image annotation. Yacine . Jernite. Text-as-Data series. September 17. 2015. What do we want from text?. Extract information. Link to other knowledge sources. Use knowledge (Wikipedia, . UpToDate,…). How do we answer those questions?. Division of Student Assessment & School Improvement. Virginia Department of Education. New . Partially Accredited . Ratings. Partially . Accredited: Approaching Benchmark-Graduation and Completion Index. Yizhou. Sun, Rick Barber, Manish Gupta, . Charu. . C. . Aggarwal. , . Jiawei. Han. 1. Content. Background and motivation. Problem definition. PathPredict. : meta path-based . relationship prediction . Alexander Kotov. 1. , . Mehedi. Hasan. 1. , . April . Carcone. 1. , Ming Dong. 1. , Sylvie Naar-King. 1. , Kathryn Brogan Hartlieb. 2. . 1 . Wayne State University. 2 . Florida International University. Classification. with Incomplete Class . Hierarchies. Bhavana Dalvi. ¶. *. , Aditya Mishra. †. , and William W. Cohen. *. ¶ . Allen Institute . for . Artificial Intelligence, . * . School Of Computer Science. Pilfered from…. NIPS 2010: Online Learning for LDA, Hoffman, Bach & . Blei. Date. . :. . 2013/11/27. Source. . :. . CIKM’13. Advisor . : . Dr.Jia. -ling, . Koh. Speaker : Wei, Chang. 1. Outline. Introduction. Approach. Experiment. Conclusion. 2. Twitter. 3. What are they talking about?. Access Pipeline Protests (NoDAPL). CS 5984/4984 Big Data Text Summarization Report. . Xiaoyu Chen*, Haitao Wang, Maanav Mehrotra, Naman Chhikara, Di Sun. {xiaoyuch, wanght, maanav, namanchhikara, sdi1995} @vt.edu. Analysis. ). ShaLi. . Limitation of PCA. The direction of maximum variance is not always good for classification. Limitation of PCA. The direction of maximum variance is not always good for classification. Unsu. pervised . approaches . for . word sense disambiguation. Under the guidance of. Slides by. Arindam. . Chatterjee. &. Salil. Joshi. Prof. . Pushpak . Bhattacharyya. May 01, 2010. roadmap. Bird’s Eye View.. Self-Learning Learning . Technique. . for. Image . Disease. . Localization. . Rushikesh. Chopade1, . Aditya. Stanam2, . Abhijeet. Patil3 & . Shrikant. Pawar4*. 1. Department of . Geology.

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