Cost sensitive hierarchical document classification to triage PubMed abstracts for manual curation
نویسندگان
چکیده
منابع مشابه
Biomedical Document Triage Based on Figure Classification
The annotation task in model organism databases is to assign attributes, such as Gene Ontology (GO) codes, to biological entities, such as genes and proteins based on the evidence found in documents or other resources. Document triage precedes an annotation task; it identifies relevant documents that can support the annotation process. Annotation in organism databases involves manual efforts of...
متن کاملHierarchical Attention Networks for Document Classification
We propose a hierarchical attention network for document classification. Our model has two distinctive characteristics: (i) it has a hierarchical structure that mirrors the hierarchical structure of documents; (ii) it has two levels of attention mechanisms applied at the wordand sentence-level, enabling it to attend differentially to more and less important content when constructing the documen...
متن کاملMultilingual Hierarchical Attention Networks for Document Classification
Hierarchical attention networks have recently achieved remarkable performance for document classification in a given language. However, when multilingual document collections are considered, training such models separately for each language entails linear parameter growth and lack of cross-language transfer. Learning a single multilingual model with fewer parameters is therefore a challenging b...
متن کاملClustering with Propagation for Hierarchical Document Classification
We address the problem of unsupervised classification of documents into a given hierarchy of concepts with few unlabeled examples. In contrast to various previous approaches where only the leaves of the hierarchy represent valid classes, we consider the situation where documents must also be classified into internal nodes. We claim that the relationships between classes are part of the a priori...
متن کاملCost-sensitive call classification
We present an efficient and effective method which extends the Boosting family of classifiers to allow the weighted classes. Typically classifiers do not treat individual classes separately. For most real world applications, this is not the case, not all classes have the same importance. The accuracy of a particular class can be more critical than others. In this paper we extend the mathematica...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2011
ISSN: 1471-2105
DOI: 10.1186/1471-2105-12-482