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Systems for inducing concept descriptions from examples are valuable tools for assisting in the task of knowledge acquisition for expert systems. This paper presents a description and empirical evaluation of a new induction system, cn2, designed for the ecient induction of simple, comprehensible production rules in domains where problems of poor description(More)
We present a theoretical and empirical framework for computing and evaluating linear projections conditional on hypothetical paths of monetary policy. A modest policy intervention does not significantly shift agents' beliefs about policy regime and does not induce the changes in behavior that Lucas (1976) emphasizes. Applied to an econometric model of U.S.(More)
Our goal is to extract answers from pre-retrieved sentences for Question Answering (QA). We construct a linear-chain Conditional Random Field based on pairs of questions and their possible answer sentences, learning the association between questions and answer types. This casts answer extraction as an answer sequence tagging problem for the first time,(More)
We complement the theory of tick-by-tick dynamics of financial markets based on a Continuous-Time Random Walk (CTRW) model recently proposed by Scalas et al [4], and we point out its consistency with the behaviour observed in the waiting-time distribution for BUND future prices traded at LIFFE, London.
and seminar participants at the IMF, WTO, Inter-American Development Bank for helpful suggestions and discussions. The authors would also like to thanks two anonymous referees and the editor (Bob Staiger) for comments that have substantially improved the paper. ABSTRACT This paper furnishes robust evidence that the WTO has had a strong positive impact on(More)
This paper presents the Seventh Recognizing Textual Entailment (RTE-7) challenge. This year's challenge replicated the exercise proposed in RTE-6, consisting of a Main Task, in which Textual Entailment is performed on a real corpus in the Update Summarization scenario; a Main subtask aimed at detecting novel information; and a KBP Validation Task, in which(More)
Building a knowledge base for a given domain traditionally involves a subject matter expert and a knowledge engineer. One of the goals of our research is to eliminate the knowledge engineer. There are at least two ways to achieve this goal: train domain experts to write axioms (<i>i.e.</i>, turn them into knowledge engineers) or create tools that allow(More)
This paper examines the induction of classification rules from examples using real-world data. Real-world data is almost always characterized by two features, which are important for the design of an induction algorithm. Firstly, there is often noise present, for example, due to imperfect measuring equipment used to collect the data. Secondly the(More)