systems. However, the clearest advantage is demonstrated in constructing non-redundant multi-document summaries, where MMR results are clearly superior to non-MMR passage selection. 2 Maximal Marginal Relevance Most modem IR search engines produce a ranked list of retrieved documents ordered by declining

classifier that evaluates the relevance of a hypertext document with respect to the focus topics, ...

are summarized and evaluated in view of this critical evidence and the 2 major candidate theories--relative speed of processing and automaticity of reading--are found to be wanting. It is concluded that recent theories placing the explanatory weight on parallel processing of the irrelevant and the relevant

in seven organizations, and results support its validity. A number of special features of the model are discussed (including its use as a basis for the diagnosis of jobs and the evaluation of job redesign projects), and the model is compared to other theories of job design. Work redesign is becoming

in normal human cognition (see Fiske& Taylor, 1984; In this article, we review research suggesting that certain illusions may be adaptive for mental health and well-being. In particular, we examine evidence that a set of interrelated positive illusions-namely, unrealistically positive self-evaluations

We present Scatter/Gather, a cluster-based document browsing method, as an alternative to ranked titles for the organization and viewing of retrieval results. We systematically evaluate Scatter/Gather in this context and find significant improvements over similarity search ranking alone

in detail the process for learning phrasal translations, the feature functions used, and the search algorithm. The evaluation of this approach is performed on three different tasks. For the German–English speech Verbmobil task, we analyze the effect of various system components. On the French

Color-based trackers recently proposed in [3,4,5] have been proved robust and versatile for a modest computational cost. They are especially appealing for tracking tasks where the spatial structure of the tracked objects exhibits such a dramatic variability that trackers based on a space

When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to address this task, for example, geometry or disk models, placing sensors at the points of highest entropy (variance

this evaluation formula with an appropriate correlation measure and a heuristic search strategy. CFS was evaluated by experiments on artificial and natural datasets. Three machine learning algorithms were used: C4.5 (a decision tree learner), IB1 (an instance based learner), and naive Bayes. Experiments