Collaborative text-annotation resource for disease-centered relation extraction from biomedical text
نویسندگان
چکیده
منابع مشابه
Collaborative text-annotation resource for disease-centered relation extraction from biomedical text
Agglomerating results from studies of individual biological components has shown the potential to produce biomedical discovery and the promise of therapeutic development. Such knowledge integration could be tremendously facilitated by automated text mining for relation extraction in the biomedical literature. Relation extraction systems cannot be developed without substantial datasets annotated...
متن کاملInformation extraction from biomedical text
Information extraction is the process of scanning text for information relevant to some interest, including extracting entities, relations, and events. It requires deeper analysis than key word searches, but its aims fall short of the very hard and long-term problem of full text understanding. Information extraction represents a midpoint on this spectrum, where the aim is to capture structured ...
متن کاملEntity- and relation extraction from biomedical text corpora
This thesis addresses the problem of named entity recognition and the problem of relation extraction from biomedical text corpora. Named entity recognition (NER) and relation extraction (RE) are two important subtasks of information extraction. The problem of entity identification from biomedical text corpora has been found to be much harder than the identification of entities in areas such as ...
متن کاملServices for annotation of biomedical text
Motivation: Text mining in the biomedical domain in recent years has focused on the development of tools for recognizing named entities and extracting relations. Such research resulted from the need for such tools as basic components for more advanced solutions. Named entity recognition, entity mention normalization, and relationship extraction now have reached a stage where they perform compar...
متن کاملEnhancing Biomedical Text Summarization Using Semantic Relation Extraction
Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extra...
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ژورنال
عنوان ژورنال: Journal of Biomedical Informatics
سال: 2009
ISSN: 1532-0464
DOI: 10.1016/j.jbi.2009.02.001