Medical Literatures on the web are the important sources to help clinicians in patient-care. Initially, the clinicians go through the author-written abstracts or summaries available with the medical articles to decide whether articles are suitable for in-depth study. Since all medical articles do not come with author written abstracts or summaries, automatic summarization of medical articles wi...

Adaptation technologies are always useful in NLP when there is discrepancy between the training scenario and use scenario. They are also effective in alleviating the data scarcity problem. Domain adaptation is the most popular kind of adaptation technologies and is intensively researched. In this talk we will introduce two other kinds of adaptation technologies: annotation adaptation and langua...

Text mining is an effective means of detecting potentially useful knowledge from large text documents. However conventional text mining technology cannot achieve high accuracy, because it cannot effectively make use of the semantic information of the text. Ontology provides theoretical basis and technical support for semantic information representation and organization. This paper improves the ...

Domain adaptation approaches seek to learn from a source domain and generalize it an unseen target domain. At present, the state-of-the-art unsupervised for subjective text classification problems leverage unlabeled data along with labeled data. In this paper, we propose novel method of single-task based on simple but effective idea diversity-based generalization that does not require still mat...

In the era of social media, a large volume data is generated by applications such as industrial internet things, IoT, Facebook, Twitter, and individual usage. Artificial intelligence big tools plays an important role in devising mechanisms for handling this vast per required usage to form information from unstructured data. When publicly available on it imperative treat carefully respect sentim...