Visualization for Relevance Assessments

Abstract Visual data exploration is a well-known technique in the data mining toolbox for analyzing and understanding large amounts of data. In information retrieval, visualization is still perceived as a front-end or user facing feature while, at the same time, it can be very effective in the back-end for data analysis. Currently, the research community does not sufficiently analyze the reasons underlying the assessments they use for evaluation, which may lead to bias or error when reporting system performance. In this paper we examine the integration of information visualization techniques for visually exploring and analyzing relevance assessments. We argue that visual tools should be integrated as a core component of the infrastructure for relevance assessment and evaluation

Human assessments of document similarity

Two studies are reported that examined the reliability of human assessments of document similarity and the association between human ratings and the results of n-gram automatic text analysis (ATA). Human interassessor reliability (IAR) was moderate to poor. However, correlations between average human ratings and n-gram solutions were strong. The average correlation between ATA and individual human solutions was greater than IAR. N-gram length influenced the strength of association, but optimum string length depended on the nature of the text (technical vs. nontechnical). We conclude that the methodology applied in previous studies may have led to overoptimistic views on human reliability, but that an optimal n-gram solution can provide a good approximation of the average human assessment of document similarity, a result that has important implications for future development of document visualization systems

Teegi: Tangible EEG Interface

We introduce Teegi, a Tangible ElectroEncephaloGraphy (EEG) Interface that enables novice users to get to know more about something as complex as brain signals, in an easy, en- gaging and informative way. To this end, we have designed a new system based on a unique combination of spatial aug- mented reality, tangible interaction and real-time neurotech- nologies. With Teegi, a user can visualize and analyze his or her own brain activity in real-time, on a tangible character that can be easily manipulated, and with which it is possible to interact. An exploration study has shown that interacting with Teegi seems to be easy, motivating, reliable and infor- mative. Overall, this suggests that Teegi is a promising and relevant training and mediation tool for the general public.Comment: to appear in UIST-ACM User Interface Software and Technology Symposium, Oct 2014, Honolulu, United State

Retrieval through explanation : an abductive inference approach to relevance feedback

Relevance feedback techniques are designed to automatically improve a system's representation of a query by using documents the user has marked as relevant. However, traditional relevance feedback models suffer from a number of limitations that restrict their potential in supporting information seeking. One of the major limitations of relevance feedback is that it does not incorporate behavioural aspects of information seeking - how and why users assess relevance. We propose that relevance feedback should be viewed as a process of explanation and demonstrate how this limitation of relevance feedback techniques can be overcome by a theory of relevance feedback based on abductive inference

Enriching Existing Test Collections with OXPath

Extending TREC-style test collections by incorporating external resources is a time consuming and challenging task. Making use of freely available web data requires technical skills to work with APIs or to create a web scraping program specifically tailored to the task at hand. We present a light-weight alternative that employs the web data extraction language OXPath to harvest data to be added to an existing test collection from web resources. We demonstrate this by creating an extended version of GIRT4 called GIRT4-XT with additional metadata fields harvested via OXPath from the social sciences portal Sowiport. This allows the re-use of this collection for other evaluation purposes like bibliometrics-enhanced retrieval. The demonstrated method can be applied to a variety of similar scenarios and is not limited to extending existing collections but can also be used to create completely new ones with little effort.Comment: Experimental IR Meets Multilinguality, Multimodality, and Interaction - 8th International Conference of the CLEF Association, CLEF 2017, Dublin, Ireland, September 11-14, 201

Aqueous Humor Outflow Structure and Function Imaging At the Bench and Bedside: A Review.

Anterior segment glaucoma clinical care and research has recently gained new focus because of novel imaging modalities and the advent of angle-based surgical treatments. Traditional investigation drawn to the trabecular meshwork now emphasizes the entire conventional aqueous humor outflow (AHO) pathway from the anterior chamber to the episcleral vein. AHO investigation can be divided into structural and functional assessments using different methods. The historical basis for studying the anterior segment of the eye and AHO in glaucoma is discussed. Structural studies of AHO are reviewed and include traditional pathological approaches to modern tools such as multi-model two-photon microscopy and optical coherence tomography. Functional assessment focuses on visualizing AHO itself through a variety of non-real-time and real-time techniques such as aqueous angiography. Implications of distal outflow resistance and segmental AHO are discussed with an emphasis on melding bench-side research to viable clinical applications. Through the development of an improved structure: function relationship for AHO in the anterior segment of the normal and diseased eye, a better understanding of the eye with improved therapeutics may be developed

Info Navigator: A visualization tool for document searching and browsing

In this paper we investigate the retrieval performance of monophonic and polyphonic queries made on a polyphonic music database. We extend the n-gram approach for full-music indexing of monophonic music data to polyphonic music using both rhythm and pitch information. We define an experimental framework for a comparative and fault-tolerance study of various n-gramming strategies and encoding levels. For monophonic queries, we focus in particular on query-by-humming systems, and for polyphonic queries on query-by-example. Error models addressed in several studies are surveyed for the fault-tolerance study. Our experiments show that different n-gramming strategies and encoding precision differ widely in their effectiveness. We present the results of our study on a collection of 6366 polyphonic MIDI-encoded music pieces