997,680 research outputs found
The role of assumptions in causal discovery
The paper looks at the conditional independence search approach to causal discovery, proposed by Spirtes et al. and Pearl and Verma, from the point of view of the mechanism-based view of causality in econometrics, explicated by Simon. As demonstrated by Simon, the problem of determining the causal structure from data is severely underconstrained and the perceived causal structure depends on the a priori assumptions that one is willing to make. I discuss the assumptions made in the independence search-based causal discovery and their identifying strength
Discovery Tools and Local Metadata Requirements in Academic Libraries
As the second decade of the twenty-first century commences, academic librarians who work to promote collection access must not only contend with a vast array of content available in a wide range of formats, but they must also ensure that new technologies developed to accommodate user search behaviors yield satisfactory outcomes. Next generation discovery tools are designed to streamline the search process and facilitate better search results by incorporating metadata from proprietary and local collections, then by providing relevancy-ranked results. This paper investigates the implications of discovery tool use for accessing materials housed in institutional repositories and special collections, in particular, how the discovery of these materials depends on local metadata creation practices. This paper surveys current research pertaining to metadata quality issues that may put unique local collections at risk for being overlooked in meta-search relevancy rankings, and considers ways in which academic libraries can address this issue as well as areas for future research
Embedding-based Scientific Literature Discovery in a Text Editor Application
Each claim in a research paper requires all relevant prior knowledge to be
discovered, assimilated, and appropriately cited. However, despite the
availability of powerful search engines and sophisticated text editing
software, discovering relevant papers and integrating the knowledge into a
manuscript remain complex tasks associated with high cognitive load. To define
comprehensive search queries requires strong motivation from authors,
irrespective of their familiarity with the research field. Moreover, switching
between independent applications for literature discovery, bibliography
management, reading papers, and writing text burdens authors further and
interrupts their creative process. Here, we present a web application that
combines text editing and literature discovery in an interactive user
interface. The application is equipped with a search engine that couples
Boolean keyword filtering with nearest neighbor search over text embeddings,
providing a discovery experience tuned to an author's manuscript and his
interests. Our application aims to take a step towards more enjoyable and
effortless academic writing.
The demo of the application (https://SciEditorDemo2020.herokuapp.com/) and a
short video tutorial (https://youtu.be/pkdVU60IcRc) are available online
From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web
A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results
Master Robotic Net
The main goal of the MASTER-Net project is to produce a unique fast sky
survey with all sky observed over a single night down to a limiting magnitude
of 19 - 20mag. Such a survey will make it possible to address a number of
fundamental problems: search for dark energy via the discovery and photometry
of supernovas (including SNIa), search for exoplanets, microlensing effects,
discovery of minor bodies in the Solar System and space-junk monitoring. All
MASTER telescopes can be guided by alerts, and we plan to observe prompt
optical emission from gamma-ray bursts synchronously in several filters and in
several polarization planes.Comment: 10 pages, 8 figure
Exploiting Social Annotation for Automatic Resource Discovery
Information integration applications, such as mediators or mashups, that
require access to information resources currently rely on users manually
discovering and integrating them in the application. Manual resource discovery
is a slow process, requiring the user to sift through results obtained via
keyword-based search. Although search methods have advanced to include evidence
from document contents, its metadata and the contents and link structure of the
referring pages, they still do not adequately cover information sources --
often called ``the hidden Web''-- that dynamically generate documents in
response to a query. The recently popular social bookmarking sites, which allow
users to annotate and share metadata about various information sources, provide
rich evidence for resource discovery. In this paper, we describe a
probabilistic model of the user annotation process in a social bookmarking
system del.icio.us. We then use the model to automatically find resources
relevant to a particular information domain. Our experimental results on data
obtained from \emph{del.icio.us} show this approach as a promising method for
helping automate the resource discovery task.Comment: 6 pages, submitted to AAAI07 workshop on Information Integration on
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Identifying common user behaviour in multilingual search logs
The LADS (Log Analysis for Digital Societies) task at CLEF
aims at investigating user actions in a multilingual setting. We carried out an analysis of search logs with the objectives of investigating how users from different linguistic or cultural backgrounds behave in search,
and how the discovery of patterns in user actions could be used for community identification. The findings confirm that users from a different background behave differently, and that there are identifiable patterns in the user actions. The findings suggest that there is scope for further investigation of how search logs can be exploited to personalise and improve cross-language search as well as improve the TEL search system
Sensor nets discover search
In the world of information discovery there are several major trends which are emerging. These include the fact that the nature of search itself is changing because our information needs are themselves becoming more complex and the data volume is increasing. Other trends are that information is increasingly being aggregated, and that search is now becoming information discovery. In this presentation I address a different kind of information source to the usual media, scientific, leisure, and entertainment information we usually consume, whose availability is now upon us, namely data gathered from sensors. This covers both the physical sensors around us which monitor our environment, our wellbeing and our activities, as well as the online sensors which monitor and track things happening elsewhere in the work and to which we have access. These sensor information sources are noisy, errorsome, unpredictable and dynamic, exactly like both our real and our virtual worlds. Several wide-ranging sensor web applications are used to demonstrate the importance of event processing in managing information discovery from the sensor web
Contextualized B2B Registries
Abstract. Service discovery is a fundamental concept underpinning the move towards dynamic service-oriented business partnerships. The business process for integrating service discovery and underlying registry technologies into business relationships, procurement and project management functions has not been examined and hence existing Web Service registries lack capabilities required by business today. In this paper we present a novel contextualized B2B registry that supports dynamic registration and discovery of resources within management contexts to ensure that the search space is constrained to the scope of authorized and legitimate resources only. We describe how the registry has been deployed in three case studies from important economic sectors (aerospace, automotive, pharmaceutical) showing how contextualized discovery can support distributed product development processes
The computer revolution in science: steps towards the realization of computer-supported discovery environments
The tools that scientists use in their search processes together form so-called discovery environments. The promise of artificial intelligence and other branches of computer science is to radically transform conventional discovery environments by equipping scientists with a range of powerful computer tools including large-scale, shared knowledge bases and discovery programs. We will describe the future computer-supported discovery environments that may result, and illustrate by means of a realistic scenario how scientists come to new discoveries in these environments. In order to make the step from the current generation of discovery tools to computer-supported discovery environments like the one presented in the scenario, developers should realize that such environments are large-scale sociotechnical systems. They should not just focus on isolated computer programs, but also pay attention to the question how these programs will be used and maintained by scientists in research practices. In order to help developers of discovery programs in achieving the integration of their tools in discovery environments, we will formulate a set of guidelines that developers could follow
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