Improving Retrieval Results with discipline-specific Query Expansion

Choosing the right terms to describe an information need is becoming more difficult as the amount of available information increases. Search-Term-Recommendation (STR) systems can help to overcome these problems. This paper evaluates the benefits that may be gained from the use of STRs in Query Expansion (QE). We create 17 STRs, 16 based on specific disciplines and one giving general recommendations, and compare the retrieval performance of these STRs. The main findings are: (1) QE with specific STRs leads to significantly better results than QE with a general STR, (2) QE with specific STRs selected by a heuristic mechanism of topic classification leads to better results than the general STR, however (3) selecting the best matching specific STR in an automatic way is a major challenge of this process.Comment: 6 pages; to be published in Proceedings of Theory and Practice of Digital Libraries 2012 (TPDL 2012

GAMLSS for high-dimensional data – a flexible approach based on boosting

Generalized additive models for location, scale and shape (GAMLSS) are a popular semi-parametric modelling approach that, in contrast to conventional GAMs, regress not only the expected mean but every distribution parameter (e.g. location, scale and shape) to a set of covariates. Current fitting procedures for GAMLSS are infeasible for high-dimensional data setups and require variable selection based on (potentially problematic) information criteria. The present work describes a boosting algorithm for high-dimensional GAMLSS that was developed to overcome these limitations. Specifically, the new algorithm was designed to allow the simultaneous estimation of predictor effects and variable selection. The proposed algorithm was applied to data of the Munich Rental Guide, which is used by landlords and tenants as a reference for the average rent of a flat depending on its characteristics and spatial features. The net-rent predictions that resulted from the high-dimensional GAMLSS were found to be highly competitive while covariate-specific prediction intervals showed a major improvement over classical GAMs

METHOD TO EMULATE THE L-BAND DIGITAL AERONAUTICAL COMMUNICATION SYSTEM FOR SESAR EVALUATION AND VERIFICATION

The VHF voice communication system currently used for air traffic control is experiencing increasing capacity problems. The “L-band Digital Aeronautical Communications System” is an upcoming technology providing an aeronautical datalink outside of the VHF band. The objective of this paper is to develop a method to emulate its communication performance. We developed a formal model of the system and implemented it on the basis of the dummynet network emulation tools. This implementation was deployed in a networking appliance and measured in a test-bed network. The results indicate that the emulator provides the performance predicted by simulations and is suitable to evaluate and verify protocols and applications envisioned to utilize this datalink

Evolution of orogenic blocking

March 1993.Includes bibliographic references.Sponsored by the National Science Foundation ATM-8713652.Sponsored by the National Science Foundation ATM-9113898