Title Goal Method Result

Slides:



Advertisements
Similar presentations
Recommender System A Brief Survey.
Advertisements

Chapter 5: Introduction to Information Retrieval
Balanced Literacy J McIntyre Belize.
Q/A System First Stage: Classification Project by: Abdullah Alotayq, Dong Wang, Ed Pham.
Part 2c: Requirements Chapter 2: How to Gather Requirements: Some Techniques to Use Chapter 3: Finding Out about the Users and the Domain Chapter 4: Finding.
A Framework for Named Entity Recognition in the Open Domain Richard Evans Research Group in Computational Linguistics University of Wolverhampton UK
Chapter 5: Information Retrieval and Web Search
Accounting for Plant Assets and Depreciation Chapter 18, Section 1 Buying Plant Assets and Paying Property Taxes.
Case Studies Dr Lee Nung Kion Faculty of Cognitive Sciences and Human Development UNIVERSITI MALAYSIA SARAWAK.
Employing EM and Pool-Based Active Learning for Text Classification Andrew McCallumKamal Nigam Just Research and Carnegie Mellon University.
Thien Anh Dinh1, Tomi Silander1, Bolan Su1, Tianxia Gong
Smart RSS Aggregator A text classification problem Alban Scholer & Markus Kirsten 2005.
computer
LESSON 3. Properties of Well-Engineered Software The attributes or properties of a software product are characteristics displayed by the product once.
Powerpoint Templates Page 1 Powerpoint Templates Scalable Text Classification with Sparse Generative Modeling Antti PuurulaWaikato University.
Enhancing Text Classifiers to Identify Disease Aspect Information Rey-Long Liu Dept. of Medical Informatics Tzu Chi University Taiwan.
Task Analysis for Instructional Design: an introduction Ganesh Padmanabhan 3/19/2004.
Multi-object Similarity Query Evaluation Michal Batko.
Chapter 4 Image Enhancement in the Frequency Domain.
1 Title Line on a Divider Slide Format >Level one bullet text for a divider slide.
Contextual Text Cube Model and Aggregation Operator for Text OLAP
?!?!??!? Teaching Your Computer to Read By Matthew Falk.
Speech Recognition through Neural Networks By Mohammad Usman Afzal Mohammad Waseem.
Presentation Title.
Presentation Title.
Mohammad Alqahtani, Dr. Eric Atwell
Teaching Reading.
classification/classify genus invertebrate kingdom phylum/phyla species vertebrate.
What Is Cluster Analysis?
Computer architecture and computer organization
SNS College of Engineering Coimbatore
Systems Biology for Translational Medicine
That’s It! I. Recognizing Arguments II. Analyzing Arguments
Logic and Computer Design Fundamentals
Functional Management
Functional Management
Functional Management
Functional Management
Functional Management
Functional Management
Techniques for Computing Limits: The Limit Laws
Effective Research-Based Strategies Marzano
Research Areas Christoph F. Eick
RECORDING THE BUYING OF A PLANT ASSET
Prepared by: Mahmoud Rafeek Al-Farra
Presentation Title goes here, Long if needed
פחת ורווח הון סוגיות מיוחדות תהילה ששון עו"ד (רו"ח) ספטמבר 2015
Classification of Matter Task Card Classification of Matter Task Card
Group 1 Group 1 Group 1 Group 1 word word word word word word word word word word word word word word word word word word word word word word word.
classification/classify genus invertebrate kingdom phylum/phyla species vertebrate.
This is the title This is a subheading This is body text Bullets 1
Суури мэдлэг Basic Knowledge
Chapter 5: Information Retrieval and Web Search
Relations, Domain and Range
Dynamic Category Profiling for Text Filtering and Classification
Presentation Title goes here, Long if needed
Higher Order Thinking Skills
Presentation By: Eryk Helenowski PURE Mentor: Vincent Bindschaedler
Mark Chavira Ulises Robles
Rey-Long Liu Dept. of Medical Informatics Tzu Chi University Taiwan
Extracting Patterns and Relations from the World Wide Web
Title Introduction: Discussion & Conclusion: Methods & Results:
Presentation Title Your information.
Unsupervised Machine Learning: Clustering Assignment
Main Title Here Topic 2 Topic 3 Topic 4 Topic 5
Incremental Context Mining for Adaptive Document Classification
THE TOPICS AND TITLES OF RESEARCH
Classification Project
Techniques for Computing Limits: The Limit Laws
Presentation transcript:

Title Goal Method Result Context-based Term Frequency Assessment for Text Classification (by Rey-Long Liu) Goal Improving various kinds of text classifiers by term context recognition (TCR) Method Employing TCR to refine term frequency (TF) assessment Applying the TF assessment to various classifiers Result A technique CTFA is developed Applicable to various kinds of text classifiers (no modification is required) No problems of data sparseness and over-fitting No need for huge memory, expensive computation, and domain-specific knowledge