Active Learning with Crowd-Sourcing Semester Project Report
نویسنده
چکیده
منابع مشابه
Active Learning and Crowd-Sourcing for Machine Translation
In recent years, corpus based approaches to machine translation have become predominant, with Statistical Machine Translation (SMT) being the most actively progressing area. Success of these approaches depends on the availability of parallel corpora. In this paper we propose Active Crowd Translation (ACT), a new paradigm where active learning and crowd-sourcing come together to enable automatic...
متن کاملScaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning
Crowd-sourcing has become a popular means of acquiring labeled data for many tasks where humans are more accurate than computers, such as image tagging, entity resolution, and sentiment analysis. However, due to the time and cost of human labor, solutions that rely solely on crowd-sourcing are oen limited to small datasets (i.e., a few thousand items). is paper proposes algorithms for integrat...
متن کاملActive Learning for Crowd-Sourced Databases
Crowd-sourcing has become a popular means of acquiring labeled data for many tasks where humans are more accurate than computers, such as image tagging, entity resolution, or sentiment analysis. However, due to the time and cost of human labor, solutions that solely rely on crowd-sourcing are often limited to small datasets (i.e., a few thousand items). This paper proposes algorithms for integr...
متن کاملOn the Effectiveness of Crowd Sourcing Avian Nesting Video Analysis at Wildlife@Home
Wildlife@Home is citizen science project developed to provide wildlife biologists a way to swiftly analyze the massive quantities of data that they can amass during video surveillance studies. The project has been active for two years, with over 200 volunteers who have participated in providing observations through a web interface where they can stream video and report the occurrences of variou...
متن کاملPronunciation learning for named-entities through crowd-sourcing
Obtaining good pronunciations for named-entities poses a challenge for automated speech recognition because namedentities are diverse in nature and origin, and new entities come up every day. In this paper, we investigate the feasibility of learning named-entity pronunciations using crowd-sourcing. By collecting audio samples from non-linguistic-expert speakers with Mechanical Turk and learning...
متن کامل