Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Support vector machines, reproducing kernel Hilbert spaces, and randomized GACV
Advances in kernel methods
Proceedings of the 10th international conference on World Wide Web
Support Vector Machines for Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-line new event detection, clustering, and tracking (information retrieval, internet)
On-line new event detection, clustering, and tracking (information retrieval, internet)
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News event detection is the task of discovering relevant, yet previously unreported real-life events and reporting it to users in human-readable form, while event tracking aims to automatically assign event labels to news stories when they arrive. A new method and system for performing the event detection and tracking task is proposed in this paper. The event detection and tracking method is based on subject extraction and an improved support vector machine (SVM), in which subject concepts can concisely and precisely express the meaning of a longer text. The improved SVM first prunes the negative examples, reserves and deletes a negative sample according to distance and class label, then trains the new set with SVM to obtain a classifier and maps the SVM outputs into probabilities. The experimental results with the real-world data sets indicate the proposed method is feasible and advanced.