Boosting Applied to Tagging and PP Attachment
نویسندگان
چکیده
Boosting is a machine learning algorithm that is not well known in computational linguistics. We apply it to part-of-speech tagging and prepositional phrase attachment. Performance is very encouraging. We also show how to improve data quality by using boosting to identify annotation errors.
منابع مشابه
Human Centered NLP with User-Factor Adaptation
We pose the general task of user-factor adaptation — adapting supervised learning models to real-valued user factors inferred from a background of their language, reflecting the idea that a piece of text should be understood within the context of the user that wrote it. We introduce a continuous adaptation technique, suited for real-valued user factors that are common in social science and brin...
متن کاملAdd-on for High Throughput Screening in Material Discovery for Organic Electronics: “Tagging” Molecules to Address the Device Considerations
This work reflects the worth of intelligent modeling in controlling the nanostructure morphology in manufacturing organic bulk heterojunction (BHJ) solar cells. It suggests the idea of screening the pool of material design possibilities inspired by machine learning. To fulfill this goal, a set of experimental data on a BHJ solar cell with a donor structure of diketopyrrolopyrrole (DDP) and ...
متن کاملAttaching Multiple Prepositional Phrases: Generalized Backed-oo Estimation
There has recently been considerable interest in the use of lexically-based statistical techniques to resolve preposition-al phrase attachments. To our knowledge , however, these investigations have only considered the problem of attaching the rst PP, i.e., in a V NP PP] conngura-tion. In this paper, we consider one technique which has been successfully applied to this problem, backed-oo estima...
متن کاملAttaching Multiple Prepositional Phrases: Generalized Backed-off Estimation
There has recently been considerable interest in the use of lexically-based statistical techniques to resolve prepositional phrase attachments. To our knowledge, however, these investigations have only considered the problem of attaching the first PP, i.e., in a [V NP PP] configuration. In this paper, we consider one technique which has been successfully applied to this problem, backed-off esti...
متن کاملWorkshop Notes of the ECML / MLnet Workshop on Empirical Learning of Natural Language Processing Tasks
This paper analyses the relation between the use of similarity in Memory-Based Learning and the notion of backed-oo smoothing in statistical language modeling. We show that the two approaches are closely related, and we argue that feature weighting methods in the Memory-Based paradigm can ooer the advantage of automatically specifying a suitable domain-speciic hierarchy between most speciic and...
متن کامل