Machine Learning
A maximum entropy approach to natural language processing
Computational Linguistics
Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
Knowledge-based metadata extraction from PostScript files
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Information retrieval on the web
ACM Computing Surveys (CSUR)
Automatic metadata generation & evaluation
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
The Perceptron Algorithm with Uneven Margins
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Maximum Entropy Markov Models for Information Extraction and Segmentation
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Metadata Based Web Mining for Relevance
IDEAS '00 Proceedings of the 2000 International Symposium on Database Engineering & Applications
A maximum entropy approach to information extraction from semi-structured and free text
Eighteenth national conference on Artificial intelligence
HICSS '98 Proceedings of the Thirty-First Annual Hawaii International Conference on System Sciences - Volume 2
Automatic document metadata extraction using support vector machines
Proceedings of the 3rd ACM/IEEE-CS joint conference on Digital libraries
Data and Metadata for Finding and Reminding
IV '99 Proceedings of the 1999 International Conference on Information Visualisation
Table extraction using conditional random fields
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
eBizSearch: a niche search engine for e-business
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
DIAL '04 Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL'04)
Statistical models for unsupervised prepositional phrase attachment
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Metaextract: an NLP system to automatically assign metadata
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
Focused named entity recognition using machine learning
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Simple BM25 extension to multiple weighted fields
Proceedings of the thirteenth ACM international conference on Information and knowledge management
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Columbia Newsblaster: multilingual news summarization on the web
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
A new approach to intranet search based on information extraction
Proceedings of the 14th ACM international conference on Information and knowledge management
Automatic categorization of figures in scientific documents
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
FLUX-CIM: flexible unsupervised extraction of citation metadata
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
A metadata generation system for scanned scientific volumes
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
Automatic metadata extraction from museum specimen labels
DCMI '08 Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications
Evaluation of an integrated multi-task machine learning system with humans in the loop
PerMIS '07 Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems
Survey measures for evaluation of cognitive assistants
PerMIS '07 Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems
Header metadata extraction from semi-structured documents using template matching
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
Proceedings of the twelfth international workshop on Web information and data management
Searching online book documents and analyzing book citations
Proceedings of the 2013 ACM symposium on Document engineering
Hi-index | 0.00 |
In this paper, we propose a machine learning approach to title extraction from general documents. By general documents, we mean documents that can belong to any one of a number of specific genres, including presentations, book chapters, technical papers, brochures, reports, and letters. Previously, methods have been proposed mainly for title extraction from research papers. It has not been clear whether it could be possible to conduct automatic title extraction from general documents. As a case study, we consider extraction from Office including Word and PowerPoint. In our approach, we annotate titles in sample documents (for Word and PowerPoint respectively) and take them as training data, train machine learning models, and perform title extraction using the trained models. Our method is unique in that we mainly utilize formatting information such as font size as features in the models. It turns out that the use of formatting information can lead to quite accurate extraction from general documents. Precision and recall for title extraction from Word is 0.810 and 0.837 respectively, and precision and recall for title extraction from PowerPoint is 0.875 and 0.895 respectively in an experiment on intranet data. Other important new findings in this work include that we can train models in one domain and apply them to another domain, and more surprisingly we can even train models in one language and apply them to another language. Moreover, we can significantly improve search ranking results in document retrieval by using the extracted titles.