A sequential algorithm for training text classifiers
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
The effect of adding relevance information in a relevance feedback environment
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
The nature of statistical learning theory
The nature of statistical learning theory
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Making large-scale support vector machine learning practical
Advances in kernel methods
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Semi-supervised support vector machines
Proceedings of the 1998 conference on Advances in neural information processing systems II
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Athena: Mining-Based Interactive Management of Text Database
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
Active + Semi-supervised Learning = Robust Multi-View Learning
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Semi-supervised Clustering by Seeding
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Partially Supervised Classification of Text Documents
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Combining Labeled and Unlabeled Data for MultiClass Text Categorization
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Using Unlabelled Data for Text Classification through Addition of Cluster Parameters
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Enhancing Supervised Learning with Unlabeled Data
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Automatic Capacity Tuning of Very Large VC-Dimension Classifiers
Advances in Neural Information Processing Systems 5, [NIPS Conference]
PAC Learning from Positive Statistical Queries
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
PEBL: positive example based learning for Web page classification using SVM
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Support Vector Machines: Training and Applications
Support Vector Machines: Training and Applications
One-class svms for document classification
The Journal of Machine Learning Research
Learning from positive and unlabeled examples
Theoretical Computer Science - Algorithmic learning theory (ALT 2000)
Learning to classify texts using positive and unlabeled data
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Editorial: special issue on learning from imbalanced data sets
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Automatic Pattern-Taxonomy Extraction for Web Mining
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Text Classification without Labeled Negative Documents
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Text Classification without Negative Examples Revisit
IEEE Transactions on Knowledge and Data Engineering
Blocking objectionable web content by leveraging multiple information sources
ACM SIGKDD Explorations Newsletter
Computer Methods and Programs in Biomedicine
Mining User preference using Spy voting for search engine personalization
ACM Transactions on Internet Technology (TOIT)
Learning Bayesian classifiers from positive and unlabeled examples
Pattern Recognition Letters
A two-step classification approach to unsupervised record linkage
AusDM '07 Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70
Learning classifiers from only positive and unlabeled data
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
SVM based adaptive learning method for text classification from positive and unlabeled documents
Knowledge and Information Systems
PE-PUC: A Graph Based PU-Learning Approach for Text Classification
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Imbalanced text classification: A term weighting approach
Expert Systems with Applications: An International Journal
Unsupervised Text Learning Based on Context Mixture Model with Dirichlet Prior
Advanced Web and NetworkTechnologies, and Applications
Learning to Find Relevant Biological Articles without Negative Training Examples
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Classification techniques with minimal labelling effort and application to medical reports
International Journal of Data Mining and Bioinformatics
Semi-supervised document retrieval
Information Processing and Management: an International Journal
Cool Blog Classification from Positive and Unlabeled Examples
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Building a Text Classifier by a Keyword and Unlabeled Documents
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Named entity mining from click-through data using weakly supervised latent dirichlet allocation
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Feature subset selection from positive and unlabelled examples
Pattern Recognition Letters
Semi-Supervised Text Classification Using Positive and Unlabeled Data
Proceedings of the 2006 conference on Advances in Intelligent IT: Active Media Technology 2006
OcVFDT: one-class very fast decision tree for one-class classification of data streams
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data
Text data acquisition for domain-specific language models
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Partially supervised sense disambiguation by learning sense number from tagged and untagged corpora
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Selecting relevant text subsets from web-data for building topic specific language models
NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
Mining linguistic cues for query expansion: applications to drug interaction search
Proceedings of the 18th ACM conference on Information and knowledge management
Active learning in partially supervised classification
Proceedings of the 18th ACM conference on Information and knowledge management
Content based image retrieval using unclean positive examples
IEEE Transactions on Image Processing
Improving Text Classification Performance with Incremental Background Knowledge
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Concept-Based, Personalized Web Information Gathering: A Survey
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Mining rough association from text documents for web information gathering
Transactions on rough sets VII
Ontology based web mining for information gathering
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
Best-match method used in co-training algorithm
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
A knowledge-based model using ontologies for personalized web information gathering
Web Intelligence and Agent Systems
Distributional similarity vs. PU learning for entity set expansion
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Expert Systems with Applications: An International Journal
Negative training data can be harmful to text classification
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Finding the storyteller: automatic spoiler tagging using linguistic cues
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
A survey of recent trends in one class classification
AICS'09 Proceedings of the 20th Irish conference on Artificial intelligence and cognitive science
Semi-Supervised Novelty Detection
The Journal of Machine Learning Research
Social negative bootstrapping for visual categorization
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Applying machine learning in accounting research
Expert Systems with Applications: An International Journal
Editorial: Classifying text streams by keywords using classifier ensemble
Data & Knowledge Engineering
Bayesian classifiers for positive unlabeled learning
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Purging false negatives in cancer diagnosis using incremental active learning
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
On positive and unlabeled learning for text classification
TSD'11 Proceedings of the 14th international conference on Text, speech and dialogue
A pairwise ranking based approach to learning with positive and unlabeled examples
Proceedings of the 20th ACM international conference on Information and knowledge management
Extracting initial and reliable negative documents to enhance classification performance
KDLL'06 Proceedings of the 2006 international conference on Knowledge Discovery in Life Science Literature
Comparison of documents classification techniques to classify medical reports
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Spying out accurate user preferences for search engine adaptation
WebKDD'04 Proceedings of the 6th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Importance-based web page classification using cost-sensitive SVM
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
A new approach for semi-supervised online news classification
HSI'05 Proceedings of the 3rd international conference on Human Society@Internet: web and Communication Technologies and Internet-Related Social Issues
Learning from positive and unlabeled examples with different data distributions
ECML'05 Proceedings of the 16th European conference on Machine Learning
Partially supervised classification – based on weighted unlabeled samples support vector machine
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
User-Interest-Based document filtering via semi-supervised clustering
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
A new PU learning algorithm for text classification
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Leveraging one-class SVM and semantic analysis to detect anomalous content
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
Protein-Protein interactions classification from text via local learning with class priors
NLDB'09 Proceedings of the 14th international conference on Applications of Natural Language to Information Systems
Query-Based video event definition using rough set theory and high-dimensional representation
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Learning from positive and unlabeled amazon reviews: towards identifying trustworthy reviewers
Proceedings of the 21st international conference companion on World Wide Web
Estimate unlabeled-data-distribution for semi-supervised PU learning
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
Similarity-based approach for positive and unlabelled learning
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Learning very fast decision tree from uncertain data streams with positive and unlabeled samples
Information Sciences: an International Journal
Predicting quality flaws in user-generated content: the case of wikipedia
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Building high-performance classifiers using positive and unlabeled examples for text classification
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
Discovering relevant features for effective query formulation
IRFC'12 Proceedings of the 5th conference on Multidisciplinary Information Retrieval
Named entity disambiguation in streaming data
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Multi-view learning from imperfect tagging
Proceedings of the 20th ACM international conference on Multimedia
Analysis of presence-only data via semi-supervised learning approaches
Computational Statistics & Data Analysis
Learning from positive and unlabelled examples using maximum margin clustering
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Automatic Item Weight Generation for Pattern Mining and its Application
International Journal of Data Warehousing and Mining
Heat pump detection from coarse grained smart meter data with positive and unlabeled learning
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning from data streams with only positive and unlabeled data
Journal of Intelligent Information Systems
Toward supervised anomaly detection
Journal of Artificial Intelligence Research
What users care about: a framework for social content alignment
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Multi-instance multi-label learning with weak label
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Instance selection and instance weighting for cross-domain sentiment classification via PU learning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Proceedings of the 7th ACM international conference on Web search and data mining
Transfer learning with one-class data
Pattern Recognition Letters
A bagging SVM to learn from positive and unlabeled examples
Pattern Recognition Letters
Expert Systems with Applications: An International Journal
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This paper studies the problem of building text classifiersusing positive and unlabeled examples. The key feature ofthis problem is that there is no negative example forlearning. Recently, a few techniques for solving thisproblem were proposed in the literature. These techniquesare based on the same idea, which builds a classifier intwo steps. Each existing technique uses a different methodfor each step. In this paper, we first introduce some newmethods for the two steps, and perform a comprehensiveevaluation of all possible combinations of methods of thetwo steps. We then propose a more principled approachto solving the problem based on a biased formulation ofSVM, and show experimentally that it is more accuratethan the existing techniques.