41 research outputs found

    One-Shot Labeling for Automatic Relevance Estimation

    Full text link
    Dealing with unjudged documents ("holes") in relevance assessments is a perennial problem when evaluating search systems with offline experiments. Holes can reduce the apparent effectiveness of retrieval systems during evaluation and introduce biases in models trained with incomplete data. In this work, we explore whether large language models can help us fill such holes to improve offline evaluations. We examine an extreme, albeit common, evaluation setting wherein only a single known relevant document per query is available for evaluation. We then explore various approaches for predicting the relevance of unjudged documents with respect to a query and the known relevant document, including nearest neighbor, supervised, and prompting techniques. We find that although the predictions of these One-Shot Labelers (1SL) frequently disagree with human assessments, the labels they produce yield a far more reliable ranking of systems than the single labels do alone. Specifically, the strongest approaches can consistently reach system ranking correlations of over 0.86 with the full rankings over a variety of measures. Meanwhile, the approach substantially increases the reliability of t-tests due to filling holes in relevance assessments, giving researchers more confidence in results they find to be significant. Alongside this work, we release an easy-to-use software package to enable the use of 1SL for evaluation of other ad-hoc collections or systems.Comment: SIGIR 202

    Physicists' Information Tasks: Structure, Length and Retrieval Performance

    Get PDF
    In this poster, we describe central aspects of 65 natural information tasks from 23 senior researchers, PhDs, and experienced MSc students from three different university departments of physics. We analyze 1) the main purpose of the information task, 2) which and how many search facets were used to describe the tasks, 3) what semantic categories were used to express the search facets, and 4) retrieval performance. Results show variety in structure and length across task descriptions and task purposes. The results indicate effect of length and, in particular, of task purpose on retrieval performance of different document description levels that should be examined further

    Does degree of work task completion influence retrieval performance?

    Full text link

    Documents and Time

    Get PDF
    This essay offers a philosophical account of time and documents. It first presents a number of theories of time and discusses how time has been applied in research on documents to date. These applications have been limited by their conceptualization of time as a physical entity. In order to extend our understanding of documental time, this paper draws from Heidegger\u27s experiential theory of time and the theory of document transaction in order to introduce a theory of documental time. In documental time, the past and future of the person and the past and future of the object cohere in a shared present. The special case of numinous document experiences—and numinous time—is also explored

    Diversifying Search Results Using Time

    No full text
    Getting an overview of a historic entity or event can be difficult in search results, especially if important dates concerning the entity or event are not known beforehand. For such information needs, users would benefit if returned results covered diverse dates, thus giving an overview of what has happened throughout history. Diversifying search results based on important dates can be a building block for applications, for instance, in digital humanities. Historians would thus be able to quickly explore longitudinal document collections by querying for entities or events without knowing associated important dates apriori. In this work, we describe an approach to diversify search results using temporal expressions (e.g., in the 1990s) from their contents. Our approach first identifies time intervals of interest to the given keyword query based on pseudo-relevant documents. It then re-ranks query results so as to maximize the coverage of identified time intervals. We present a novel and objective evaluation for our proposed approach. We test the effectiveness of our methods on the New York Times Annotated corpus and the Living Knowledge corpus, collectively consisting of around 6 million documents. Using history-oriented queries and encyclopedic resources we show that our method indeed is able to present search results diversified along time

    Report from Dagstuhl Seminar 23031: Frontiers of Information Access Experimentation for Research and Education

    Full text link
    This report documents the program and the outcomes of Dagstuhl Seminar 23031 ``Frontiers of Information Access Experimentation for Research and Education'', which brought together 37 participants from 12 countries. The seminar addressed technology-enhanced information access (information retrieval, recommender systems, natural language processing) and specifically focused on developing more responsible experimental practices leading to more valid results, both for research as well as for scientific education. The seminar brought together experts from various sub-fields of information access, namely IR, RS, NLP, information science, and human-computer interaction to create a joint understanding of the problems and challenges presented by next generation information access systems, from both the research and the experimentation point of views, to discuss existing solutions and impediments, and to propose next steps to be pursued in the area in order to improve not also our research methods and findings but also the education of the new generation of researchers and developers. The seminar featured a series of long and short talks delivered by participants, who helped in setting a common ground and in letting emerge topics of interest to be explored as the main output of the seminar. This led to the definition of five groups which investigated challenges, opportunities, and next steps in the following areas: reality check, i.e. conducting real-world studies, human-machine-collaborative relevance judgment frameworks, overcoming methodological challenges in information retrieval and recommender systems through awareness and education, results-blind reviewing, and guidance for authors.Comment: Dagstuhl Seminar 23031, report
    corecore