Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Vasileios Hatzivassiloglou"'
Publikováno v:
Journal of Biomedical Informatics. 40(2):150-159
Biomedical abbreviations and acronyms are widely used in biomedical literature. Since many of them represent important content in biomedical literature, information retrieval and extraction benefits from identifying the meanings of those terms. On th
Publikováno v:
ACM Transactions on Information Systems. 24:380-404
Abbreviations and acronyms are widely used in the biomedical literature and many of them represent important biomedical concepts. Because many abbreviations are ambiguous (e.g., CAT denotes both chloramphenicol acetyl transferase and computed axial t
Autor:
Pauline Kra, Shawn M. Gomez, George Hripcsak, Ivan Iossifov, Michael Krauthammer, Andrey Rzhetsky, Vasileios Hatzivassiloglou, Carol Friedman
Publikováno v:
ISMB
Motivation: Knowledge on interactions between molecules in living cells is indispensable for theoretical analysis and practical applications in modern genomics and molecular biology. Building such networks relies on the assumption that the correct mo
Autor:
Kristian J. Concepcion, Kathleen R. McKeown, Desmond A. Jordan, Steven Feiner, Vasileios Hatzivassiloglou
Publikováno v:
Journal of the American Medical Informatics Association. 8:267-280
Objective: The authors present a system that scans electronic records from cardiac surgery and uses inference rules to identify and classify abnormal events (e.g., hypertension) that may occur during critical surgical points (e.g., start of bypass).
Autor:
Luis Gravano, Eduard Hovy, Judith L. Klavans, Vasileios Hatzivassiloglou, Andrew Philpot, Yigal Arens, José Luis Ambite
Publikováno v:
Computer. 34:47-54
Using technology developed at the Digital Government Research Center, a team of researchers is seeking to make government statistical data more accessible through the Internet. In collaboration with government experts, they are conducting research in
Autor:
Carl Sable, Vasileios Hatzivassiloglou
Publikováno v:
International Journal on Digital Libraries. 3:261-275
The rapid expansion of multimedia digital collections brings to the fore the need for classifying not only text documents but their embedded non-textual parts as well. We propose a model for basing classification of multimedia on broad, non-topical f
Publikováno v:
The Information Retrieval Series ISBN: 1402040261
Computing Attitude and Affect in Text
Computing Attitude and Affect in Text
A new task is identified in the ongoing analysis of opinions: finding propositional opinions, sentential complement clauses of verbs such as “believe” or “claim” that express opinions, and the holders of these opinions. An extension of semant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02760fdbc4ab2b9e6613a5e99101556c
https://doi.org/10.1007/1-4020-4102-0_11
https://doi.org/10.1007/1-4020-4102-0_11
Publikováno v:
ACL
Recently, many Natural Language Processing (NLP) applications have improved the quality of their output by using various machine learning techniques to mine Information Extraction (IE) patterns for capturing information from the input text. Currently
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3444e0614232e4a32ef905f013454e94
Autor:
Andrey Rzhetsky, Carol Friedman, Ivan Iossifov, Michael Krauthammer, Joel S. Bader, Kevin P. White, Vasileios Hatzivassiloglou
Publikováno v:
Bioinformatics (Oxford, England). 20(8)
Summary: Information on molecular networks, such as networks of interacting proteins, comes from diverse sources that contain remarkable differences in distribution and quantity of errors. Here, we introduce a probabilistic model useful for predictin