Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Towards Multi-paper Summarization Using Reference Information
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Towards an Automated Citation Classifier
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Automatic classification of citation function
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
TCP over Multi-Hop Wireless Networks: The Impact of MAC Level Interactions
ADHOC-NOW '09 Proceedings of the 8th International Conference on Ad-Hoc, Mobile and Wireless Networks
NLPIR4DL '09 Proceedings of the 2009 Workshop on Text and Citation Analysis for Scholarly Digital Libraries
The importance of fine-grained cue phrases in scientific citations
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
Proceedings of the 10th annual joint conference on Digital libraries
Proceedings of the 6th International Conference on Semantic Systems
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Detecting citation types using finite-state machines
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Classifying sentences using induced structure
SPIRE'05 Proceedings of the 12th international conference on String Processing and Information Retrieval
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Academic publishers' full text databases are an important part of the deep Web for researchers and a potentially valuable resource for automated extraction of scientific knowledge. Recently, some major publishers have provided Web APIs for accessing their article databases, thus allowing the development of Web applications to mine these resources. However the task of knowledge discovery from academic articles, particularly with citations remains a challenge. We present in this paper our research work taken up for identifying contexts associated with sentences in academic articles and use of this information to provide information services for the research community. To this end, we propose an annotation scheme for sentences in academic articles. We also describe our experiments with conditional random fields for sentence classification. Finally, we present CitContExt -- a citation context extraction application developed based on the techniques discussed above.