Contextual information and assessor characteristics in complex question answering

The ciqa track investigates the role of interaction in answering complex questions: questions that relate two or more entities by some specified relationship. In our submission to the first ciqa track we were interested in the interplay between groups of variables: variables describing the question creators, the questions asked and the presentation of answers to the questions. We used two interaction forms - html questionnaires completed before answer assessment - to gain contextual information from the answer assessors to better understand what factors influence assessors when judging retrieved answers to complex questions. Our results indicate the importance of understanding the assessor's personal relationship to the question - their existing topical knowledge for example - and also the presentation of the answers - contextual information about the answer to aid in the assessment of the answer

Intra-assessor consistency in question answering

In this paper we investigate the consistency of answer assessment in a complex question answering task examining features of assessor consistency, types of answers and question type

Discovery of Raman-scattered lines in the massive luminous emission-line star LHA 115-S 18

LHA 115-S 18 is a very peculiar emission-line star exhibiting the B[e] phenomenon. Located in the Small Magellanic Cloud, its spectrum shows features of an extremely wide range of excitation and ionization stages, extending from highly ionized atomic lines (Si IV, C IV, He II) in the UV and optical regions to molecular emission bands of CO and TiO in the optical and IR regions. The most distinguishing spectral characteristic of LHA 115-S 18 is the high variability detected in the He II {\lambda}4686 emission line, which can be a very conspicuous or completely invisible feature. In this work, we report on another peculiarity of LHA 115-S 18. From high-resolution optical spectra taken between 2000 and 2008, we discovered the appearance and strengthening of two emission features at {\lambda}6825 \AA, and {\lambda}7082 \AA,, which we identified as Raman-scattered lines. This is the first time these lines have been detected in the spectrum of a massive luminous B[e] star. As the classification of LHA 115-S 18 is highly controversial, we discuss how the discovery of the appearance of Raman-scattered lines in this peculiar star might help us to solve this puzzle.Comment: Letter accepted for publication in MNRAS. 5 pages, 3 figure

Towards Building Economic Models of Conversational Search

Various conceptual and descriptive models of conversational search have been proposed in the literature -- while useful, they do not provide insights into how interaction between the agent and user would change in response to the costs and benefits of the different interactions. In this paper, we develop two economic models of conversational search based on patterns previously observed during conversational search sessions, which we refer to as: Feedback First where the agent asks clarifying questions then presents results, and Feedback After where the agent presents results, and then asks follow up questions. Our models show that the amount of feedback given/requested depends on its efficiency at improving the initial or subsequent query and the relative cost of providing said feedback. This theoretical framework for conversational search provides a number of insights that can be used to guide and inform the development of conversational search agents. However, empirical work is needed to estimate the parameters in order to make predictions specific to a given conversational search setting.Comment: To appear in ECIR 202

Detection of curved lines with B-COSFIRE filters: A case study on crack delineation

The detection of curvilinear structures is an important step for various computer vision applications, ranging from medical image analysis for segmentation of blood vessels, to remote sensing for the identification of roads and rivers, and to biometrics and robotics, among others. %The visual system of the brain has remarkable abilities to detect curvilinear structures in noisy images. This is a nontrivial task especially for the detection of thin or incomplete curvilinear structures surrounded with noise. We propose a general purpose curvilinear structure detector that uses the brain-inspired trainable B-COSFIRE filters. It consists of four main steps, namely nonlinear filtering with B-COSFIRE, thinning with non-maximum suppression, hysteresis thresholding and morphological closing. We demonstrate its effectiveness on a data set of noisy images with cracked pavements, where we achieve state-of-the-art results (F-measure=0.865). The proposed method can be employed in any computer vision methodology that requires the delineation of curvilinear and elongated structures.Comment: Accepted at Computer Analysis of Images and Patterns (CAIP) 201