We extend the event tracking task of Topic Detection and Tracking (TDT) to create a framework in which a user can highlight relevant passages in addition to specifying the relevance of documents. A dual framework of combined document and passage feedback improves performance over a state-of-the-art system without feedback by over 70% . Although annotators vary in the content and length of the p...

In this paper, we describe an innovative, pneumatically-actuated haptic feedback glove. We also examine the effect of haptic feedback from that device on a test subject’s ability to properly grasp a virtual remote object. Two parameters relevant to grasping were examined: success and force control. The success parameter is a indication of whether the virtual object was grasped, not grasped or d...

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly i...

Relevance feedback (RF) has been an effective query modification approach to improving the performance of information retrieval (IR) by interactively asking a user whether a set of documents are relevant or not to a given query concept. The conventional RF algorithms either converge slowly or cost a user’s additional efforts in reading irrelevant documents. This paper surveys several RF algorit...

The neural basis of feedback expectation, which is crucial in learning theory, has only been minimally studied. Stimulus-preceding negativity (SPN), an ERP component that appears prior to the presentation of feedback, has been proposed as being related to feedback expectation. The present study showed, for the first time, amplitude modulations of the SPN component during learning acquisition in...

We report results of beam tests of the FONT3 intratrain position feedback system prototype at the Accelerator Test Facility (ATF) at KEK. The feedback system incorporates a novel beam position monitor (BPM) processor with latency below 5 nanoseconds, and a kicker driver amplifier with similar low latency. The 56 nanosecond-long bunchtrain in the ATF extraction line was used to test the prototyp...

Motivated by anecdotal evidence, we hypothesize that an egocentric approach is more appropriate and relevant to providing fuel efficiency feedback than a systemic approach. In this paper we describe a proposed study to test this hypothesis, and present the design of a fuel efficiency feedback system for public transit bus drivers.

Relevance feedback has been used to effectively improve the retrieval performance of CBIR. In this paper, we propose a bag-based relevance feedback framework for largescale CBIR. We use kmeans-based clustering method to partition the large-scale image database based on (noisy) textual and low-level visual features. When the user selects relevant and irrelevant images as their feedback, we intro...

This paper discusses the approximate and feedback relevant parametric identi cation of the radial servo system present in a Compact Disc player. In this application the problem of approximate identi cation based on data from closed loop experiments will be analyzed to nd a nite dimensional linear time invariant discrete time model, suitable for model-based control design. The feedback relevant ...

In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image retrieval (Cbir), is proposed. This approach combines the merits of semi-supervised learning and active learning. In detail, in each round of relevance feedback, two simple learners are trained from the labeled data, i.e. images f...