Investigating multi-label classification for human values
نویسندگان
چکیده
منابع مشابه
Investigating Multi-Label Classification for Human Values
This paper describes the development of a scalable process for people and machines working together to identify sections of text that reflect specific human values. A total of 2,005 sentences from 28 prepared testimonies presented before hearings on Net neutrality were manually annotated for one or more of ten human values using an annotation frame based on experience annotating similar content...
متن کاملExploiting Associations between Class Labels in Multi-label Classification
Multi-label classification has many applications in the text categorization, biology and medical diagnosis, in which multiple class labels can be assigned to each training instance simultaneously. As it is often the case that there are relationships between the labels, extracting the existing relationships between the labels and taking advantage of them during the training or prediction phases ...
متن کاملAggregating Human-Expert Opinions for Multi-Label Classification
This paper introduces a multi-label classification problem to the field of human computation. The problem involves training data such that each instance belongs to a set of classes. The true class sets of all the instances are provided together with their estimations presented by m human experts. Given the training data and the class-set estimates of the m experts for a new instance, the multil...
متن کاملMulti-Objective Multi-Label Classification
Multi-label classification refers to the task of predicting potentially multiple labels for a given instance. Conventional multi-label classification approaches focus on the single objective setting, where the learning algorithm optimizes over a single performance criterion (e.g. Ranking Loss) or a heuristic function. The basic assumption is that the optimization over one single objective can i...
متن کاملStreaming Multi-label Classification
This paper presents a new experimental framework for studying multi-label evolving stream classification, with efficient methods that combine the best practices in streaming scenarios with the best practices in multi-label classification. Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non strea...
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: Proceedings of the American Society for Information Science and Technology
سال: 2010
ISSN: 0044-7870
DOI: 10.1002/meet.14504701116