Conferences, Lectures, & Seminars
Events for February
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AI Seminar-Fabio Rinaldi:
Fri, Feb 14, 2014 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Fabio Rinaldi, Senior Researcher, Lecturer, and PI at the University of Zurich, Switzerland
Talk Title: OntoGene & SASEBio: biomedical text mining research at UZH
Series: AISeminar
Abstract: There are vast amounts of knowledge encoded in the scientific literature which could be made more easily accessible and useful to a broader range of users through the application of more effective software tools. Text mining is a new discipline which seeks to provide ways to find, extract and manipulate the knowledge which still remains to a large extent hidden in the literature.
Text mining tools can already provide a very effective way to extract some specific types of information, but are not yet so advanced that their results can be used without human verification by domain experts. Therefore one very promising area of application of text mining technologies is within the process of database curation.
The need to efficiently retrieve key information derived from experimental results, and published in the scientific literature, is of fundamental importance in biology. In order to help biologists, as well as in some cases medical practitioners, to efficiently find such
information in the enormous quantity of published articles, several public and private institutions fund the construction and maintenance of specialized databases, which have the role to collect specific knowledge items and provide them in an easily accessible format. There are several dozens of such databases, each specializing in a
particular domain of the life sciences [1].
In this talk I will describe text mining activities conducted by my research group at the University of Zurich (OntoGene: www.ontogene.org). The OntoGene group is supported by the Swiss National Science Foundation (project SASEBIO: Semi-Automated Semantic
Enrichment of the Biomedical Literature) and by Roche Pharmaceuticals. The SASEBio project focuses in particular on applications of text mining technologies to the process of biomedical database curation.
The OntoGene team has participated in several competitive evaluations of biomedical text mining technologies, obtaining competitive results in all of them. Some of these results will be discussed in the talk. Additionally, I will present ODIN (OntoGene Document Inspector), an interactive tool which allows database curators to leverage upon the results of the OntoGene text mining system and use them in their
curation tasks.
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[1] Xose M. Fernandez-Suarez, Daniel J. Rigden, and Michael Y. Galperin. The 2014 nucleic acids research database issue and an updated NAR online molecular biology database collection. Nucleic Acids Research, 42(D1):D1-D6, 2014
The OntoGene text mining system is based on a scalable entity recognition component with a semi-automated organism-based disambiguation module, an in-house dependency parser, and a flexible relation mining approach. The OntoGene team has participated in several biomedical text mining challenges (BioCreative, BioNLP,
CALBC), obtaining competitive results in all of them. Some of these results will be discussed in the talk.
The OntoGene Document Inspector (ODIN) is an interactive tool which allows database curators to leverage upon the results of the OntoGene text mining system and use them in their curation tasks. One recent version of the system has been tested in the curation process of the Pharmacogenomics Knowledge Base (PharmGKB), and another version
adapted for the Comparative Toxicogenomics Database in the context of
a BioCreative challenge.
Biography: Fabio Rinaldi is the leader of the OntoGene research group at the University of Zurich and the principal investigator of the SASEBio project. He holds an MSc in Computer Science (University of Udine, Italy) and a PhD in Computational Linguistics (University of Zurich, Switzerland). He is author of more than 100 scientific publications (including 19 journal papers) dealing with topics such as Ontologies, Text Mining, Text Classification, Document and Knowledge Management, Language Resources and Terminology.
Host: David Chiang
Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=7bf4d5a5d7404d249254a2b96006ea6e1dLocation: Information Science Institute (ISI) - 11th fl Large CR
WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=7bf4d5a5d7404d249254a2b96006ea6e1d
Audiences: Everyone Is Invited
Contact: Alma Nava / Information Sciences Institute
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
NL Seminar- Hal Daume: "Predicting Linguistic Structures Accurately and Efficiently"
Fri, Feb 14, 2014 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Hal Daume, University of Maryland
Talk Title: "Predicting Linguistic Structures Accurately and Efficiently"
Series: Natural Language Seminar
Abstract: Many classic problems in natural language processing can be cast as building mapping from a complex input (e.g., a sequence of words) to a complex output (e.g., a syntax tree or semantic graph). This task is challenging both because language is ambiguous (learning difficulties) and represented with discrete combinatorial structures (computational difficulties). Often these are at odds: the features you want to add to decrease learning difficulties cause nontrivial additional structure yielding worse computational difficulties.
I will begin by discussing algorithms that side-step the issue of combinatorial blowup and aim to predict an output structure directly. I will then present approaches that explicitly learn to trade-off accuracy and efficiency, applied to a variety of linguistic phenomena. Moreover, I will show that in some cases, we can actually obtain a model that is faster and more accurate by exploiting smarter learning algorithms.
Biography: http://www.umiacs.umd.edu/~hal/
Host: Yang Gao
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
AI Seminar- Big Data Curation
Thu, Feb 20, 2014 @ 02:30 PM - 03:30 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Renee Miller , Bell Canada Chair of Information Systems University of Toronto
Talk Title: Big Data Curation
Series: Artificial Intelligence Seminar
Abstract: A new mode of inquiry, problem solving, and decision making has become pervasive in our society, consisting of applying computational, mathematical, and statistical models to infer actionable information from large quantities of data. This paradigm, often called Big Data Analytics or simply Big Data, requires new forms of data management to deal with the volume, variety, and velocity of Big Data. Many of these data management problems can be described as data curation. Data curation includes all the processes needed for principled and controlled data creation, maintenance, and management, together with the capacity to add value to data. In this talk, I describe our experience in curating several open data sets. I overview how we have adapted some of the traditional solutions for aligning data and creating semantics to account for (and take advantage of) Big Data.
Biography: Renée J. Miller received BS degrees in Mathematics and in Cognitive Science from the Massachusetts Institute of Technology. She received her MS and PhD degrees in Computer Science from the University of Wisconsin in Madison, WI. She is a Fellow of the Royal Society of Canada (Canada's National Academy) and the Bell Canada Chair of Information Systems at the University of Toronto. She received the US Presidential Early Career Award for Scientists and Engineers (PECASE) , the highest honor bestowed by the United States government on outstanding scientists and engineers beginning their careers and the National Science Foundation Career Award. She is a Fellow of the ACM, the President of the VLDB Endowment, and was the Program Chair for ACM SIGMOD 2011 in Athens, Greece. Her work has focused on the long-standing open problem of data integration and has achieved the goal of building practical data integration systems. She and her co-authors received the ICDT Test-of-Time Award for their influential 2003 paper establishing the foundations of data exchange.
http://dblab.cs.toronto.edu/~miller/
Host: Craig Knoblock
Webcast: TBALocation: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
WebCast Link: TBA
Audiences: Everyone Is Invited
Contact: Peter Zamar
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
NL Seminar- Kenji Sagae:Dependency parsing with directed graph output
Fri, Feb 28, 2014 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Kenji Sagae, USC/ ICT
Talk Title: Dependency parsing with directed graph output
Series: Natural Language Seminar
Abstract: Most data-driven dependency parsing approaches assume that the structure of sentences is represented as trees. Although trees have several desirable properties from a computational perspective, the structure of linguistic phenomena that go beyond shallow syntax often cannot be fully captured by tree representations. I will describe data-driven dependency parsing approaches that produce more general graphs as output, and present results obtained with these approaches on predicate-argument structures extracted from CCG and HPSG datasets.
Biography: Kenji Sagae is a Research Scientist in the Institute for Creative Technolgies at the University of Southern California, and a Research Assistant Professor in the USC Computer Science Department. He received his PhD from Carnegie Mellon University in 2006. Prior to joining USC in 2008, he was a research associate at the University of Tokyo. His main area of research is Natural Language Processing, focusing on data-driven approaches for syntactic parsing, predicate-argument analysis and discourse processing. His current work includes the application of these techniques in analysis of personal narratives in blog posts, the study of child language, spoken dialogue systems, and multimodal processing.
Home Page
http://ict.usc.edu/profile/kenji-sagae/
Host: Kevin Knight & Yang Gao
More Info: http://nlg.isi.edu/nl-seminar/
Location: 11th Flr Conf Rm # 1135, Marina Del Rey @ ISI-Info Sciences Inst.
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
