A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Classifying news stories using memory based reasoning
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Machine Learning
A hybrid user model for news story classification
UM '99 Proceedings of the seventh international conference on User modeling
A statistical learning learning model of text classification for support vector machines
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Asymptotic behaviors of support vector machines with Gaussian kernel
Neural Computation
A simple rule-based part of speech tagger
HLT '91 Proceedings of the workshop on Speech and Natural Language
Automated story capture from conversational speech
Proceedings of the 3rd international conference on Knowledge capture
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Automated story capture from internet weblogs
Proceedings of the 4th international conference on Knowledge capture
The importance of syntactic parsing and inference in semantic role labeling
Computational Linguistics
Design challenges and misconceptions in named entity recognition
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
DBpedia: a nucleus for a web of open data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
A multi-pass sieve for coreference resolution
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Stanford's multi-pass sieve coreference resolution system at the CoNLL-2011 shared task
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
Folktale classification using learning to rank
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
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A story is defined as "an actor(s) taking action(s) that culminates in a resolution(s)." In this paper, we investigate the utility of standard keyword based features, statistical features based on shallow-parsing (such as density of POS tags and named entities), and a new set of semantic features to develop a story classifier. This classifier is trained to identify a paragraph as a "story," if the paragraph contains mostly story(ies). Training data is a collection of expert-coded story and non-story paragraphs from RSS feeds from a list of extremist web sites. Our proposed semantic features are based on suitable aggregation and generalization of $$ triplets that can be extracted using a parser. Experimental results show that a model of statistical features alongside memory-based semantic linguistic features achieves the best accuracy with a Support Vector Machine (SVM) based classifier.