Automatic construction of known-item finding test beds

This work is an initial study on the utility of automatically generated queries for evaluating known-item retrieval and how such queries compare to real queries. The main advantage of automatically generating queries is that for any given test collection numerous queries can be produced at minimal cost. For evaluation, this has huge ramifications as state-of-the-art algorithms can be tested on different types of generated queries which mimic particular querying styles that a user may adopt. Our approach draws upon previous research in IR which has probabilistically generated simulated queries for other purposes [2, 3]

Building simulated queries for known-item topics: an analysis using six european languages

There has been increased interest in the use of simulated queries for evaluation and estimation purposes in Information Retrieval. However, there are still many unaddressed issues regarding their usage and impact on evaluation because their quality, in terms of retrieval performance, is unlike real queries. In this paper, we focus on methods for building simulated known-item topics and explore their quality against real known-item topics. Using existing generation models as our starting point, we explore factors which may influence the generation of the known-item topic. Informed by this detailed analysis (on six European languages) we propose a model with improved document and term selection properties, showing that simulated known-item topics can be generated that are comparable to real known-item topics. This is a significant step towards validating the potential usefulness of simulated queries: for evaluation purposes, and because building models of querying behavior provides a deeper insight into the querying process so that better retrieval mechanisms can be developed to support the user

Feather Structure and Behavioral Patterns in Seabirds

The structural details of the flight and contour feathers of seabirds closely match the requirements of their habitats and feeding habits. They serve a variety of functions ranging from intraspecific signaling to such physical qualities as thermal insulation, water repellency and resistance to impact. It comes as no surprise, therefore, that they are composed of an array of elements that confer these qualities to the optimal benefit of their avian bearer. In this chapter, the physical bases for these functions are provided in both mathematical and evolutionary terms. Some functions excel at the expense of others, and many species have evolved an optimal balance between functions in terms of both feather microstructure and behavioral patterns that suit their specific habitat and feeding habits. The effects of mechanical forces on feathers are presented in terms of the impact of diving, plunging and alighting, and the structural properties in seabird feathers identifiable as adaptations to these forces. Finally, the way oiling affects the water repellency and resistance of feathers is discussed. It is concluded that the flight and contour feathers exhibit morphological and mechanical features that are advantageous for specific habitats and feeding techniques

A modal characterization of Peirce algebras

Peirce algebras combine sets, relations and various operations linking the two in a unifying setting.This note offers a modal perspective on Peirce algebras.It uses modal logic to characterize the full Peirce algebras