Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Howard R. Turtle"'
Autor:
Howard R. Turtle, Jasy Liew Suet Yan
Publikováno v:
2021 International Conference on Computer & Information Sciences (ICCOINS).
We explore a set of machine learning experiments in fine-grained emotion classification to test different proportion of positive and negative samples in the training data with the goal to examine if class imbalance affects classifier performance. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7feefdd018f3c350703a182b8e9bce1e
https://doi.org/10.1109/iccoins49721.2021.9497181
https://doi.org/10.1109/iccoins49721.2021.9497181
Autor:
Howard R. Turtle, W. Bruce Croft
Publikováno v:
SIGIR
The use of inference networks to support document retrieval is introduced. A network-basead retrieval model is described and compared to conventional probabilistic and Boolean models.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a4c0a20337a42fe1a328ce5710c79463
https://doi.org/10.1145/3130348.3130361
https://doi.org/10.1145/3130348.3130361
Autor:
Howard R. Turtle, Jasy Liew Suet Yan
Publikováno v:
2019 1st International Conference on Artificial Intelligence and Data Sciences (AiDAS).
This study investigates the effect of diverse training samples on machine learning model performance for fine-grained emotion classification. Using four different sampling strategies (random sampling, sampling by topic and two variations of sampling
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d1ddb47fc389ac0eb02ad5394fbfb61
https://doi.org/10.1109/aidas47888.2019.8970953
https://doi.org/10.1109/aidas47888.2019.8970953
Autor:
Xiaozhong Liu, Howard R. Turtle
Publikováno v:
Journal of the American Society for Information Science and Technology. 64:1557-1576
User interest as a very dynamic information need is often ignored in most existing information retrieval systems. In this research, we present the results of experiments designed to evaluate the performance of a real-time interest model (RIM) that at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37d54ca6b13d726504d7bb3ea0ca1274
https://doi.org/10.1002/asi.22862
https://doi.org/10.1002/asi.22862
Autor:
Jasy Suet Yan Liew, Howard R. Turtle
Publikováno v:
SRW@HLT-NAACL
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f37e127e80434b4dfaf6817455a607c
https://doi.org/10.18653/v1/n16-2011
https://doi.org/10.18653/v1/n16-2011
Autor:
David J. Harper, Ellen M. Voorhees, David Lewis, Chris Buckley, Wessel Kraaij, Dragomir R. Radev, Thomas Hofmann, Nicholas J. Belkin, Ralph Weischedel, Liz Liddy, Jinxi Xu, Susan T. Dumais, Andrew McCallum, R. Manmatha, Alan F. Smeaton, R. Schwartz, Donna Harman, Victor Lavrenko, Norbert Fuhr, Jay Ponte, Mark Sanderson, Salim Roukos, ChengXiang Zhai, James Allan, Bruce Croft, Djoerd Hiemstra, Stephen Robertson, Howard R. Turtle, Jay Aslam, Roni Rosenfeld, Philip Resnik, Eduard Hovy, John Lafferty, Amit Singhal, John M. Prager, Jamie Callan
Publikováno v:
ACM SIGIR Forum. 37:31-47
Information retrieval (IR) research has reached a point where it is appropriate to assess progress and to define a research agenda for the next five to ten years. This report summarizes a discussion of IR research challenges that took place at a rece
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c841ec49e148a5164ef66667d37e1db
https://doi.org/10.1145/945546.945549
https://doi.org/10.1145/945546.945549
Publikováno v:
ACM Transactions on Information Systems. 17:367-405
The inference network model of information retrieval allows a probabilistic interpretation of query operators. In particular, Boolean query operators are conveniently modeled as link matrices of the Bayesian Network. Prior work has shown, however, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99c8ea2ffde09be8e6d6b619918a9f57
https://doi.org/10.1145/326440.326444
https://doi.org/10.1145/326440.326444
Autor:
James Flood, Howard R. Turtle
Publikováno v:
Information Processing & Management. 31:831-850
This paper discusses the two major query evaluation strategies used in large text retrieval systems and analyzes the performance of these strategies. We then discuss several optimization techniques that can be used to reduce evaluation costs and pres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8afc5825d591200c17f7790f55335e9
https://doi.org/10.1016/0306-4573(95)00020-h
https://doi.org/10.1016/0306-4573(95)00020-h
Autor:
Howard R. Turtle
Publikováno v:
Artificial Intelligence and Law. 3:5-54
The ability to find relevant materials in large document collections is a fundamental component of legal research. The emergence of large machine-readable collections of legal materials has stimulated research aimed at improving the quality of the to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6849252e2b5341b7930880357e95c6e8
https://doi.org/10.1007/bf00877694
https://doi.org/10.1007/bf00877694
Autor:
Jonathan W, Keeling, Anne M, Turner, Eileen E, Allen, Steven A, Rowe, Jacqueline A, Merrill, Elizabeth D, Liddy, Howard R, Turtle
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium. 2011
Grey literature is information not available through commercial publishers. It is a sizable and valuable information source for public health (PH) practice but because documents are not formally indexed the information is difficult to locate. Public
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::03cf09246169274a16a53edef871f202
https://pubmed.ncbi.nlm.nih.gov/22195125
https://pubmed.ncbi.nlm.nih.gov/22195125