XML Matchers: approaches and challenges

Schema Matching, i.e. the process of discovering semantic correspondences between concepts adopted in different data source schemas, has been a key topic in Database and Artificial Intelligence research areas for many years. In the past, it was largely investigated especially for classical database models (e.g., E/R schemas, relational databases, etc.). However, in the latest years, the widespread adoption of XML in the most disparate application fields pushed a growing number of researchers to design XML-specific Schema Matching approaches, called XML Matchers, aiming at finding semantic matchings between concepts defined in DTDs and XSDs. XML Matchers do not just take well-known techniques originally designed for other data models and apply them on DTDs/XSDs, but they exploit specific XML features (e.g., the hierarchical structure of a DTD/XSD) to improve the performance of the Schema Matching process. The design of XML Matchers is currently a well-established research area. The main goal of this paper is to provide a detailed description and classification of XML Matchers. We first describe to what extent the specificities of DTDs/XSDs impact on the Schema Matching task. Then we introduce a template, called XML Matcher Template, that describes the main components of an XML Matcher, their role and behavior. We illustrate how each of these components has been implemented in some popular XML Matchers. We consider our XML Matcher Template as the baseline for objectively comparing approaches that, at first glance, might appear as unrelated. The introduction of this template can be useful in the design of future XML Matchers. Finally, we analyze commercial tools implementing XML Matchers and introduce two challenging issues strictly related to this topic, namely XML source clustering and uncertainty management in XML Matchers.Comment: 34 pages, 8 tables, 7 figure

Fast, Accurate Thin-Structure Obstacle Detection for Autonomous Mobile Robots

Safety is paramount for mobile robotic platforms such as self-driving cars and unmanned aerial vehicles. This work is devoted to a task that is indispensable for safety yet was largely overlooked in the past -- detecting obstacles that are of very thin structures, such as wires, cables and tree branches. This is a challenging problem, as thin objects can be problematic for active sensors such as lidar and sonar and even for stereo cameras. In this work, we propose to use video sequences for thin obstacle detection. We represent obstacles with edges in the video frames, and reconstruct them in 3D using efficient edge-based visual odometry techniques. We provide both a monocular camera solution and a stereo camera solution. The former incorporates Inertial Measurement Unit (IMU) data to solve scale ambiguity, while the latter enjoys a novel, purely vision-based solution. Experiments demonstrated that the proposed methods are fast and able to detect thin obstacles robustly and accurately under various conditions.Comment: Appeared at IEEE CVPR 2017 Workshop on Embedded Visio

Government expenditures and unemployment: A DSGE perspective

In a New Keynesian DSGE model with labor market frictions and liquidity-constrained consumers aggregate unemployment is likely to increase due to a non-persistent government spending shock. Furthermore, the group of asset-holding households reacts very differently from the group of liquidity-constrained consumers implying that the unemployment rate is likely to decrease for asset-holding households, while it increases among liquidity-constrained consumers. The main driver of our results is the marginal utility of consumption which moves in opposite directions for the two types. Regarding the model's parameters, we find that the size of the fiscal (unemployment) multiplier increases with i) highly sticky prices, ii) high degrees of risk aversion, iii) low convexity in labor disutility iv) high replacement rates, and v) debt-financed expenditures. --Search and matching,government spending shocks,unemployment.

The new keynesian approach to dynamic general equilibrium modeling: models, methods, and macroeconomic policy evaluation

This chapter aims to provide a hands-on approach to New Keynesian models and their uses for macroeconomic policy analysis. It starts by reviewing the origins of the New Keynesian approach, the key model ingredients and representative models. Building blocks of current-generation dynamic stochastic general equilibrium (DSGE) models are discussed in detail. These models address the famous Lucas critique by deriving behavioral equations systematically from the optimizing and forward-looking decision-making of households and firms subject to well-defined constraints. State-of-the-art methods for solving and estimating such models are reviewed and presented in examples. The chapter goes beyond the mere presentation of the most popular benchmark model by providing a framework for model comparison along with a database that includes a wide variety of macroeconomic models. Thus, it offers a convenient approach for comparing new models to available benchmarks and for investigating whether particular policy recommendations are robust to model uncertainty. Such robustness analysis is illustrated by evaluating the performance of simple monetary policy rules across a range of recently-estimated models including some with financial market imperfections and by reviewing recent comparative findings regarding the magnitude of government spending multipliers. The chapter concludes with a discussion of important objectives for on-going and future research using the New Keynesian framework

Equilibrium unemployment, job flows and inflation dynamics

In order to explain the joint fluctuations of output, inflation and the labor market, this paper first develops a general equilibrium model that integrates a theory of equilibrium unemployment into a monetary model with nominal price rigidities. Then, it estimates a set of structural parameters characterizing the dynamics of the labor market using an application of the minimum distance estimation. The estimated model can explain the cyclical behavior of employment, hours per worker, job creation and job destruction conditional on a shock to monetary policy. Moreover, allowing for variation of the labor input at the extensive margin leads to a significantly lower elasticity of marginal costs with respect to output. This helps to explain the sluggishness of inflation and the persistence of output after a monetary policy shock. The ability of the model to account for the joint dynamics of output and inflation rely on its ability to explain the dynamics in the labor market. JEL Classification: E32, J41, J64, E52, E31business cycles, inflation, monetary policy, Search and Matching Models