214,905 research outputs found
From extinction learning to anxiety treatment: mind the gap
Laboratory models of extinction learning in animals and humans have the potential to illuminate methods for improving clinical treatment of fear-based clinical disorders. However, such translational research often neglects important differences between threat responses in animals and fear learning in humans, particularly as it relates to the treatment of clinical disorders. Specifically, the conscious experience of fear and anxiety, along with the capacity to deliberately engage top-down cognitive processes to modulate that experience, involves distinct brain circuitry and is measured and manipulated using different methods than typically used in laboratory research. This paper will identify how translational research that investigates methods of enhancing extinction learning can more effectively model such elements of human fear learning, and how doing so will enhance the relevance of this research to the treatment of fear-based psychological disorders.Published versio
ANTIQUE: A Non-Factoid Question Answering Benchmark
Considering the widespread use of mobile and voice search, answer passage
retrieval for non-factoid questions plays a critical role in modern information
retrieval systems. Despite the importance of the task, the community still
feels the significant lack of large-scale non-factoid question answering
collections with real questions and comprehensive relevance judgments. In this
paper, we develop and release a collection of 2,626 open-domain non-factoid
questions from a diverse set of categories. The dataset, called ANTIQUE,
contains 34,011 manual relevance annotations. The questions were asked by real
users in a community question answering service, i.e., Yahoo! Answers.
Relevance judgments for all the answers to each question were collected through
crowdsourcing. To facilitate further research, we also include a brief analysis
of the data as well as baseline results on both classical and recently
developed neural IR models
Our ten years of work on transparet box business simulation
Traditional business games are of the so-called black-box type (BBBS=Black box business
simulator); that is to say, the internal structure which generates the results of the simulation after
decision-making is not known. As a result, the player normally operates by trial and error and bases
his decisions on the symptoms of the problem (the observed behaviors of the system's variables)
and not on the real causes of the problem (the system's structure). Since 1988 José A.D. Machuca
has insisted that the business games based on System Dynamics models should be Transparent-box
business simulators (TBBSs). That means that, during the game, the user has access to the structure
of the underlying model and is able to relate it to the observed behaviors. The hypothesis is that
such transparency would facilitate causal reflection and favor systemic learning of business
problems.
In 1990, the G.I.D.E.A.O. Research Group took action on this idea and centered one of its
lines of research on this matter, with three main objectives: a) Creation of TBBSs, b) Introduction
of TBBSs in undergraduate and graduate Management courses as well as in executive training, c)
Experimentation in controlled environments in order to test the hypothesis mentioned in the above
paragraph. Now, ten years after the birth of the idea, we would like to share in this paper the results
obtained during that period
Using the Annotated Bibliography as a Resource for Indicative Summarization
We report on a language resource consisting of 2000 annotated bibliography
entries, which is being analyzed as part of our research on indicative document
summarization. We show how annotated bibliographies cover certain aspects of
summarization that have not been well-covered by other summary corpora, and
motivate why they constitute an important form to study for information
retrieval. We detail our methodology for collecting the corpus, and overview
our document feature markup that we introduced to facilitate summary analysis.
We present the characteristics of the corpus, methods of collection, and show
its use in finding the distribution of types of information included in
indicative summaries and their relative ordering within the summaries.Comment: 8 pages, 3 figure
Enabling Distributed Knowledge Management: Managerial and Technological Implications
In this paper we show that the typical architecture of current KM systems re.ects an objectivistic epistemology and a traditional managerial control paradigm. We argue that such an objectivistic epistemology is inconsistent with many theories on the nature of knowledge, in which subjectivity and sociality are taken as essential features of knowledge creation and sharing. We show that adopting such a new epistemological view has dramatic consequences at an architectural, managerial and technological level
The use of implicit evidence for relevance feedback in web retrieval
In this paper we report on the application of two contrasting types of relevance feedback for web retrieval. We compare two systems; one using explicit relevance feedback (where searchers explicitly have to mark documents relevant) and one using implicit relevance feedback (where the system endeavours to estimate relevance by mining the searcher's interaction). The feedback is used to update the display according to the user's interaction. Our research focuses on the degree to which implicit evidence of document relevance can be substituted for explicit evidence. We examine the two variations in terms of both user opinion and search effectiveness
Browsing and searching e-encyclopaedias
Educational websites and electronic encyclopaedias employ many of the same design elements, such as hyperlinks, frames and search mechanisms. This paper asks to what extent recommendations from the world of web design can be applied to e-encyclopaedias, through an evaluation of users' browsing and searching behaviour in the free, web-based versions of Encyclopaedia Britannica, the Concise Columbia Encyclopaedia and Microsoft's Encarta. It is discovered that e-encyclopaedias have a unique set of design requirements, as users' expectations are inherited from the worlds of both web and print
The impact of the mode of thought in complex decisions: intuitive decisions are better
A number of recent studies have reported that decision quality is enhanced under conditions of inattention or distraction (unconscious thought; Dijksterhuis, 2004; Dijksterhuis and Nordgren, 2006; Dijksterhuis et al., 2006). These reports have generated considerable controversy, for both experimental (problems of replication) and theoretical reasons (interpretation). Here we report the results of four experiments. The first experiment replicates the unconscious thought effect, under conditions that validate and control the subjective criterion of decision quality. The second and third experiments examine the impact of a mode of thought manipulation (without distraction) on decision quality in immediate decisions. Here we find that intuitive or affective manipulations improve decision quality compared to analytic/deliberation manipulations. The fourth experiment combines the two methods (distraction and mode of thought manipulations) and demonstrates enhanced decision quality, in a situation that attempts to preserve ecological validity. The results are interpreted within a framework that is based on two interacting subsystems of decision-making: an affective/intuition based system and an analytic/deliberation system
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