863 research outputs found
Broad expertise retrieval in sparse data environments
Expertise retrieval has been largely unexplored on data other than the W3C collection. At the same time, many intranets of universities and other knowledge-intensive organisations offer examples of relatively small but clean multilingual expertise data, covering broad ranges of expertise areas. We first present two main expertise retrieval tasks, along with a set of baseline approaches based on generative language modeling, aimed at finding expertise relations between topics and people. For our experimental evaluation, we introduce (and release) a new test set based on a crawl of a university site. Using this test set, we conduct two series of experiments. The first is aimed at determining the effectiveness of baseline expertise retrieval methods applied to the new test set. The second is aimed at assessing refined models that exploit characteristic features of the new test set, such as the organizational structure of the university, and the hierarchical structure of the topics in the test set. Expertise retrieval models are shown to be robust with respect to environments smaller than the W3C collection, and current techniques appear to be generalizable to other settings
Two-sorted metric temporal logic
AbstractTemporal logic has been successfully used for modeling and analyzing the behavior of reactive and concurrent systems. Standard temporal logic is inadequate for real-time applications because it only deals with qualitative timing properties. This is overcome by metric temporal logics which offer a uniform logical framework in which both qualitative and quantitative timing properties can be expressed by making use of a parameterized operator of relative temporal realization.In this paper we deal with completeness issues for basic systems of metric temporal logic ādespite their relevance, such issues have been ignored or only partially addressed in the literature. We view metric temporal logics as two-sorted formalisms having formulae ranging over time instants and parameters ranging over an (ordered) abelian group of temporal displacements. We first provide an axiomatization of the pure metric fragment of the logic, and prove its soundness and completeness. Then, we show how to obtain the metric temporal logic of linear orders by adding an ordering over displacements. Finally, we consider general metric temporal logics allowing quantification over algebraic variables and free mixing of algebraic formulae and temporal propositional symbols
When Inverse Propensity Scoring does not Work: Affine Corrections for Unbiased Learning to Rank
Contrastive Explanations for Large Errors in Retail Forecasting Predictions through Monte Carlo Simulations
When Inverse Propensity Scoring does not Work: Affine Corrections for Unbiased Learning to Rank
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