1,022 research outputs found

    Searching and Stopping: An Analysis of Stopping Rules and Strategies

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    Searching naturally involves stopping points, both at a query level (how far down the ranked list should I go?) and at a session level (how many queries should I issue?). Understanding when searchers stop has been of much interest to the community because it is fundamental to how we evaluate search behaviour and performance. Research has shown that searchers find it difficult to formalise stopping criteria, and typically resort to their intuition of what is "good enough". While various heuristics and stopping criteria have been proposed, little work has investigated how well they perform, and whether searchers actually conform to any of these rules. In this paper, we undertake the first large scale study of stopping rules, investigating how they influence overall session performance, and which rules best match actual stopping behaviour. Our work is focused on stopping at the query level in the context of ad-hoc topic retrieval, where searchers undertake search tasks within a fixed time period. We show that stopping strategies based upon the disgust or frustration point rules - both of which capture a searcher's tolerance to non-relevance - typically result in (i) the best overall performance, and (ii) provide the closest approximation to actual searcher behaviour, although a fixed depth approach also performs remarkably well. Findings from this study have implications regarding how we build measures, and how we conduct simulations of search behaviours

    The arguments of associations

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    This chapter considers associative solutions to “non‐linear” discrimination problems, such as negative patterning (A+ and B+ vs AB‐) and the biconditional discrimination (AB+ and CD+ vs AC‐ and BD‐). It is commonly assumed that the solution to these discriminations requires “configural” elements that are added to the compound of two stimuli. However, these discriminations can be solved by assuming that some elements of each stimulus are suppressed when two stimuli are presented in compound. Each of these approaches can solve patterning and biconditional discriminations because they allow some elements, as the arguments of associations, to have differential “presence” on reinforced versus nonreinforced trials, and thus differential associability and control over responding. The chapter then presents a more specific version of one of these models, describing how interactions between stimuli, particularly the competition for attention, provide a mechanism whereby some elements are more suppressed than others when stimuli are presented simultaneously as a compound

    Weak Liouville-Arnold Theorems & Their Implications

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    This paper studies the existence of invariant smooth Lagrangian graphs for Tonelli Hamiltonian systems with symmetries. In particular, we consider Tonelli Hamiltonians with n independent but not necessarily involutive constants of motion and obtain two theorems reminiscent of the Liouville-Arnold theorem. Moreover, we also obtain results on the structure of the configuration spaces of such systems that are reminiscent of results on the configuration space of completely integrable Tonelli Hamiltonians.Comment: 24 pages, 1 figure; v2 corrects typo in online abstract; v3 includes new title (was: A Weak Liouville-Arnold Theorem), re-arrangement of introduction, re-numbering of main theorems; v4 updates the authors' email and physical addresses, clarifies notation in section 4. Final versio

    Modeling Concurrency in Parallel Debugging

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    We propose a description language, Data Path Expressions (DPEs), for modeling the behavior of parallel programs. We have designed DPEs as a high-level debugging language, where the debugging paradigm is for the programmer to describe the expected program behavior and for the debugger to compare the actual program behavior during execution to detect program errors. We classify DPEs into five subclasses according to syntactic criteria, and characterize their semantics in terms of a hierarchy of extended Petri Net models. The characterization demonstrates the power of DPEs for modeling (true) concurrency. We also present predecessor automata as a mechanism for implementing the third subclass of DPEs, which expresses bounded parallelism. Predecessor automata extend finite state automata to recognize or generate partial ordering graphs as well as strings, and provide efficient event recognizers for parallel debugging. We briefly describe the application of DPEs race conditions, deadlock and starvation
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