Year: 2011
Type: dissertation
Abstract: Recent advances in machine learning have enabled the training of increasingly complex information retrieval models. This dissertation proposes principled approaches to formalize the learning problems for information retrieval, with an eye towards developing a unified learning framework. This will conceptually simplify the overall development process, making it easier to reason about higher level goals and properties of the retrieval system. This dissertation advocates two complementary approaches, structured prediction and interactive learning, to learn feature-rich retrieval models that can perform well in practice.
Source: eCommons (Cornell University)
Authors: Thorsten Joachims, Yisong Yue
Institution: Cornell University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W2126218310