Selective relevance feedback using term characteristics

This paper presents a new relevance feedback technique; selectively combining evidence based on the usage of terms within documents. By considering how terms are used within documents, we can better describe the features that might make a document relevant and thus improve retrieval effectiveness. In this paper we present an initial, experimental investigation of this technique, incorporating new and existing measures for describing the information content of a document. The results from these experiments positively support our hypothesis that extending relevance feedback to take into account how terms are used within documents can improve the performance of relevance feedback

Combining and selecting characteristics of information use

In this paper we report on a series of experiments designed to investigate the combination of term and document weighting functions in Information Retrieval. We describe a series of weighting functions, each of which is based on how information is used within documents and collections, and use these weighting functions in two types of experiments: one based on combination of evidence for ad-hoc retrieval, the other based on selective combination of evidence within a relevance feedback situation. We discuss the difficulties involved in predicting good combinations of evidence for ad-hoc retrieval, and suggest the factors that may lead to the success or failure of combination. We also demonstrate how, in a relevance feedback situation, the relevance assessments can provide a good indication of how evidence should be selected for query term weighting. The use of relevance information to guide the combination process is shown to reduce the variability inherent in combination of evidence

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

Formal models, usability and related work in IR (editorial for special edition)

The Glasgow IR group has carried out both theoretical and empirical work, aimed at giving end users efficient and effective access to large collections of multimedia data

Finding Relevance, Competence, and Enjoyment: The Development of Domain Identification and Interest in First-Year Science Majors

The purpose of this qualitative study was to examine how first-year college students perceive their development of domain identification with, and interest in, their prospective science major during their initial year of college. Four themes emerged from the coding and analysis of interviews with eight first-year science students: Self-Definition in Flux, Feeling Competent, Expressing Interest through Enjoyment, and Relevant to Me. These themes were mainly consistent with the current model of domain identification (Osborne & Jones, 2011) but differ from the current model of interest development (Hidi & Renninger, 2006). Theoretical and practical implications are included for faculty and advisors working with first-year science students

Probabilistic learning for selective dissemination of information

New methods and new systems are needed to filter or to selectively distribute the increasing volume of electronic information being produced nowadays. An effective information filtering system is one that provides the exact information that fulfills user's interests with the minimum effort by the user to describe it. Such a system will have to be adaptive to the user changing interest. In this paper we describe and evaluate a learning model for information filtering which is an adaptation of the generalized probabilistic model of information retrieval. The model is based on the concept of 'uncertainty sampling', a technique that allows for relevance feedback both on relevant and nonrelevant documents. The proposed learning model is the core of a prototype information filtering system called ProFile

Generating indicative-informative summaries with SumUM

We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies

A Vertical PRF Architecture for Microblog Search

In microblog retrieval, query expansion can be essential to obtain good search results due to the short size of queries and posts. Since information in microblogs is highly dynamic, an up-to-date index coupled with pseudo-relevance feedback (PRF) with an external corpus has a higher chance of retrieving more relevant documents and improving ranking. In this paper, we focus on the research question:how can we reduce the query expansion computational cost while maintaining the same retrieval precision as standard PRF? Therefore, we propose to accelerate the query expansion step of pseudo-relevance feedback. The hypothesis is that using an expansion corpus organized into verticals for expanding the query, will lead to a more efficient query expansion process and improved retrieval effectiveness. Thus, the proposed query expansion method uses a distributed search architecture and resource selection algorithms to provide an efficient query expansion process. Experiments on the TREC Microblog datasets show that the proposed approach can match or outperform standard PRF in MAP and NDCG@30, with a computational cost that is three orders of magnitude lower.Comment: To appear in ICTIR 201

Multidisciplinary Consideration of Potential Pathophysiologic Mechanisms of Paradoxical Erythema with Topical Brimonidine Therapy.

Rosacea is a chronic inflammatory disease with transient and non-transient redness as key characteristics. Brimonidine is a selective α2-adrenergic receptor (AR) agonist approved for persistent facial erythema of rosacea based on significant efficacy and good safety data. The majority of patients treated with brimonidine report a benefit; however, there have been sporadic reports of worsening erythema after the initial response. A group of dermatologists, receptor physiology, and neuroimmunology scientists met to explore potential mechanisms contributing to side effects as well as differences in efficacy. We propose the following could contribute to erythema after application: (1) local inflammation and perivascular inflammatory cells with abnormally functioning ARs may lead to vasodilatation; (2) abnormal saturation and cells expressing different AR subtypes with varying ligand affinity; (3) barrier dysfunction and increased skin concentrations of brimonidine with increased actions at endothelial and presynaptic receptors, resulting in increased vasodilation; and (4) genetic predisposition and receptor polymorphism(s) leading to different smooth muscle responses. Approximately 80% of patients treated with brimonidine experience a significant improvement without erythema worsening as an adverse event. Attention to optimizing skin barrier function, setting patient expectations, and strategies to minimize potential problems may possibly reduce further the number of patients who experience side effects.FundingGalderma International S.A.S., Paris, France