Author:
Amini Massih R.,Usunier Nicolas,Gallinari Patrick
Publisher
Springer Berlin Heidelberg
Reference29 articles.
1. Amini, M.-R., Gallinari, P.: The Use of unlabeled data to improve supervised learning for text summarization. In: Proceedings of the 25 th ACM SIGIR, pp. 105–112 (2002)
2. Aslam, J.A., Montague, M.: Models for metasearch. In: Proceedings of the 24 th annual international ACM SIGIR conference on Research and development in information retrieval (2001)
3. Caillet, M., Pessiot, J.-F., Amini, M.-R., Gallinari, P.: Unsupervised Learning with Term Clustering for Thematic Segmentation of Texts. In: Proceedings of RIAO (2004)
4. Collins, M.: Ranking algorithms for named-entity extraction: Boosting and the voted perceptron. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, ACL-2002 (2002)
5. Chuang, W.T., Yang, J.: Extracting sentence segments for text summarization: a machine learning approach. In: Proceedings of the 23 th ACM SIGIR, pp. 152–159 (2000)
Cited by
13 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Development Of Text Characterization Using Natural Language Processing Techniques;2023 International Conference on Computer Communication and Informatics (ICCCI);2023-01-23
2. Summary-Based Document Classification;Advances in Intelligent Systems and Computing;2018
3. Query-oriented Unsupervised Multi-document Summarization on Big Data;Proceedings of the 7th International Conference on Computing Communication and Networking Technologies;2016-07-06
4. An Abstract-Based Approach for Text Classification;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2016
5. How can catchy titles be generated without loss of informativeness?;Expert Systems with Applications;2014-03