Many private and/or public organizations have been reported to create and monitor targeted Twitter streams to collect and understand users’ opinions about the organizations. Tar...
Linear models have enjoyed great success in structured prediction in NLP. While a lot of progress has been made on efficient training with several loss functions, the problem of ...
People tweet more than 100 Million times daily, yielding a noisy, informal, but sometimes informative corpus of 140-character messages that mirrors the zeitgeist in an unprecedent...
We use search engine results to address a particularly difficult cross-domain language processing task, the adaptation of named entity recognition (NER) from news text to web que...
The two most important tasks in entity information summarization from the Web are named entity recognition and relation extraction. Little work has been done toward an integrated ...
We describe our contribution to the Generation Challenge 2010 for the tasks of Named Entity Recognition and coreference detection (GREC-NER). To extract the NE and the referring e...
This report describes the methods and results of a system developed for the GREC Named Entity Recognition and GREC Named Entity Regeneration Challenges 2010. We explain our proces...
Nicole L. Sparks, Charles F. Greenbacker, Kathleen...
Named entity recognition is important for semantically oriented retrieval tasks, such as question answering, entity retrieval, biomedical retrieval, trend detection, and event and...
Valentin Jijkoun, Mahboob Alam Khalid, Maarten Mar...
In this paper, we present classifiers ensemble approaches for biomedical named entity recognition. Generalized Winnow, Conditional Random Fields, Support Vector Machine, and Maxim...
Background: One step in the model organism database curation process is to find, for each article, the identifier of every gene discussed in the article. We consider a relaxation ...