We study the problem of web search result diversification in the case where intent based relevance scores are available. A diversified search result will hopefully satisfy the information need of user-L.s who may have different intents. In this context, we first analyze the properties of an intent-based metric, ERR-IA, to measure relevance and diversity altogether. We argue that this is a better metric than some previously proposed intent aware metrics and show that it has a better correlation with abandonment rate. We then propose an algorithm to rerank web search results based on optimizing an objective function corresponding to this metric and evaluate it on shopping related queries.
In practical classification, there is often a mix of learnable and unlearnable classes and only a classifier above a minimum performance threshold can be deployed. This problem is exacerbated if the training set is created by active learning. The bias of actively learned training sets makes it hard to determine whether a class has been learned. We give evidence that there is no general and efficient method for reducing the bias and correctly identifying classes that have been learned. However, we characterize a number of scenarios where active learning can succeed despite these difficulties.
Background-The spread of activation between the right atrium (RA) and left atrium (LA), particularly along the right and left aspects of the interatrial septum, is not clear. Methods and Results-Basket-shaped catheters carrying 64 electrodes were deployed into both the RA and LA of 10 dogs.Position and orientation of the baskets were determined by fluoroscopy and echocardiography. Basket unipolar electrograms were simultaneously recorded in each dog during sinus rhythm, right ventricular pacing, and pacing of the right septum through the basket in the superior and inferior regions. Isochrone maps depicting all aspects of the atria, including the septum, were compared. During sinus rhythm and superior right septal pacing, wave fronts propagated predominantly from superior to inferior regions on both the right and left septum. However, activation of the left septum was delayed compared with the right septum. During right ventricular pacing and inferior right septal pacing, activation of the septum was discordant; 1 wave front propagated rapidly on the right septum from inferior to superior regions, whereas 2 opposing wave fronts originated on the left septum in both the superior and inferior regions. The left septum was activated predominantly by the superior wave front. Activation of the left septum was completed in a significantly shorter time during pacing of the right septum in the inferior region compared with the superior region. Conclusions-In dogs, activation of the right and left aspects of the interatrial septum is discordant. Electrical connections are present between the RA and LA in regions superior as well as inferior to the septum. (Circulation. 1999;100:312-319.)
Numeric regularization methods for solving the inverse problem of electrocardiography in realistic volume conductor models have been mostly limited to uniform regularization in the spatial domain. A method of spatial regularization (SR) was developed and tested in canine, where each spatial spectral component of the volume conductor model was considered separately, and a SR operator was selected based on explicit a posteriori criterion at each time instant through the heartbeat. The inverse problem was solved in the left ventricle by reconstructing endocardial surface electrograms based on cavitary electrograms measured with the use of a noncontact, multielectrode probe. The results were validated based on electrograms measured in situ at the same endocardial locations using an integrated, multielectrode basket-catheter. A probe-endocardium three-dimensional model was determined from multiplane fluoroscopic images. The boundary element method was applied to solve the boundary value problem and derive the relationship between endocardial and probe potentials. Endocardial electrograms were reconstructed during both normal and paced rhythms using SR as well as standard, uniform, zeroth-order Tikhonov (ZOT) regularization. Compared to endocardial electrograms measured by the basket, electrograms reconstructed using SR [relative error (RE) = 0.32, correlation coefficient (CC) = 0.97, activation error = 3.3 ms] were superior to electrograms reconstructed using ZOT regularization (RE = 0.59, CC = 0.79, activation error = 4.9 ms). Therefore, regularization based on spatial spectral components of the model improves the solution of the inverse problem of electrocardiography compared to uniform regularization.
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