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Full-Text Articles in Library and Information Science
Evaluation Of Restricted Domain Question-Answering Systems, Anne R. Diekema, Ozgur Yilmazel, Elizabeth D. Liddy
Evaluation Of Restricted Domain Question-Answering Systems, Anne R. Diekema, Ozgur Yilmazel, Elizabeth D. Liddy
School of Information Studies - Faculty Scholarship
Question-Answering (QA) evaluation efforts have largely been tailored to open-domain systems. The TREC QA test collections contain newswire articles and the accompanying queries cover a wide variety of topics. While some apprehension about the limitations of restricted-domain systems is no doubt justified, the strict promotion of unlimited domain QA evaluations may have some unintended consequences. Simply applying the open domain QA evaluation paradigm to a restricted-domain system poses problems in the areas of test question development, answer key creation, and test collection construction. This paper examines the evaluation requirements of restricted domain systems. It incorporates evaluation criteria identified by users …
What Do You Mean? Finding Answers To Complex Questions, Anne R. Diekema, Ozgur Yilmazel, Jiangping Chen, Sarah Harwell, Elizabeth D. Liddy, Lan He
What Do You Mean? Finding Answers To Complex Questions, Anne R. Diekema, Ozgur Yilmazel, Jiangping Chen, Sarah Harwell, Elizabeth D. Liddy, Lan He
School of Information Studies - Faculty Scholarship
This paper illustrates ongoing research and issues faced when dealing with real-time questions in the domain of Reusable Launch Vehicles (aerospace engineering). The question- answering system described in this paper is used in a collaborative learning environment with real users and live questions. The paper describes an analysis of these more complex questions as well as research to include the user in the question-answering process by implementing a question negotiation module based on the traditional reference interview.
A Breadth Of Nlp Applications, Elizabeth D. Liddy
A Breadth Of Nlp Applications, Elizabeth D. Liddy
School of Information Studies - Faculty Scholarship
The Center for Natural Language Processing (CNLP) was founded in September 1999 in the School of Information Studies, the “Original Information School”, at Syracuse University. CNLP’s mission is to advance the development of human-like, language understanding software capabilities for government, commercial, and consumer applications. The Center conducts both basic and applied research, building on its recognized capabilities in Natural Language Processing. The Center’s seventeen employees are a mix of doctoral students in information science or computer engineering, software engineers, linguistic analysts, and research engineers.