PPT-Chapter 16: Text Mining for Translational Bioinformatics

Author : danika-pritchard | Published Date : 2016-07-30

1 Overview This presentation is for chapter 16 which discuss Chapter 16 Text Mining for Translational Bioinformatics 1 terminologies 2 definitions 2uses cases

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "Chapter 16: Text Mining for Translationa..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Chapter 16: Text Mining for Translational Bioinformatics: Transcript

1 Overview This presentation is for chapter 16 which discuss Chapter 16 Text Mining for Translational Bioinformatics 1 terminologies 2 definitions 2uses cases and applications 3evaluation techniques and evaluation metrics. Opportunities and Barriers. John . McNaught. Deputy Director. National Centre for Text Mining. John.McNaught@manchester.ac.uk. Topics. What is text mining? (briefly). What can it offer? (selectively). Tagging & Sequence Labeling. Hongning Wang. CS@UVa. What is POS . t. agging. Raw Text. Pierre . Vinken. , 61 years old , will join the board as a nonexecutive director Nov. 29 .. Pierre_. NNP. . AD103 - Friday, 3pm-4pm. Ben . Langhinrichs. President of Genii Software. Introduction. Ben Langhinrichs, Genii Software. When I am not developing software, I write children’s books and draw pictures.. Presentation by:. ABHISHEK KAMAT. ABHISHEK MADHUSUDHAN. SUYAMEENDRA WADKI. 1. Introduction. Mining the data to find interesting patterns, useful insights, customer data and their relationship - data mining . “The . word cloud . technique . first originated online in the 1990s as tag clouds (famously described as “the mullets of the . Internet”), . which were used to display the popularity of keywords in bookmarks. High-throughput Data Analysis. Literature Study. Data Mining . Functional Genomics Analysis. Vector NTI Advance®. Software. License type. License number. 2008. 2009. 2010. 2011. 2012. 2013. 2014. Galaxy. Cases . and Capabilities. Dec 8, 2016. Kayvis Damptey. Jie Zhang. What is Text Mining?. Text Mining uses documents to identify insightful patterns within the text. Thus allowing managers to summarize/organize huge collections of documents and automate detection based on useful linguistic patterns.. What Is . T. ext . M. ining?. Also known as . Text Data Mining. Process of . examining large collections of . unstructured. textual . resources in order to generate new information, typically using specialized computer software. Solution. Low rank matrix approximation. Imagine this is our observed term-document matrix. Imagine this is *true* concept-document matrix. Random noise over the word selection in each document. CS@UVa. Diane Litman. Professor, Computer Science Department . Senior Scientist, Learning Research & Development Center . Co-Director, Intelligent Systems Program. University of Pittsburgh. Pittsburgh, . CS@UVa. Today’s lecture. Support vector machines. Max margin classifier. Derivation of linear SVM. Binary and multi-class cases. Different types of losses in discriminative models. Kernel method. Non-linear SVM. April 15th Section 1: Introduction and biological databases.. Section 2: Sequence alignment.. Section 3: Gene and promoter prediction.. Section 4: Molecular phylogenetics.. Section 5: Structural Bioinformatics. http://www.cs.uic.edu/~. liub. CS583, Bing Liu, UIC. 2. General Information. Instructor: Bing Liu . Email: liub@cs.uic.edu . Tel: (312) 355 1318 . Office: SEO 931 . Lecture . times: . 9:30am-10:45am.

Download Document

Here is the link to download the presentation.
"Chapter 16: Text Mining for Translational Bioinformatics"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.