207164100
Clustering short texts using wikipedia
Subscribers to the popular news or blog feeds (RSS/Atom) often face the problem of information overload as these feed sources usually deliver large number of items periodically. One solution to this problem could be clustering similar items in the feed reader to make the information more manageable for a user. Clustering items at the feed reader end is a challenging task as usually only a small part of the actual article is received through the feed. In this paper, we propose a method of improving the accuracy of clustering short texts by enriching their representation with additional features from Wikipedia. Empirical results indicate that this enriched representation of text items can substantially improve the clustering accuracy when compared to the conventional bag of words representation.
37839097
Retaining personal expression for social search
Web is being extensively used for personal expression, which includes ratings, reviews, recommendations, blogs. This user created content, e.g. book review on Amazon.com, becomes the property of the website, and the user often does not have easy access to it. In some cases, user's feedback may get averaged with feedback from other users e.g. ratings of a video. We argue that the creator of such content needs to be able to retain (a link to) her created content. We introduce the concept of MEB which is a user controlled store of such retained links. A MEB allows a user to access/share all the reviews she has given on different websites. With this capability users can allow their friends to search through their feedback. Searching through one's social network allows harnessing the power of social networks where known relationships provide the context & trust necessary to interpret feedback.
32641793
Document Summarization using Wikipedia
Although most of the developing world is likely to first access the Internet through mobile phones, mobile devices are constrained by screen space, bandwidth and limited attention span. Single document summarization techniques have the potential to simplify information consumption on mobile phones by presenting only the most relevant information contained in the document. In this paper we present a language independent single-document summarization method. We map document sentences to semantic concepts in Wikipedia and select sentences for the summary based on the frequency of the mapped-to concepts. Our evaluation on English documents using the ROUGE package indicates our summarization method is competitive with the state of the art in single document summarization.
6504247
Hardware Diagnosis as Program Debugging
Horn clauses provide a useful framework for writing executable structural representations for digital circuits. This paper discusses how these representations can be used to diagnose faulty circuits using algorithmic program debugging techniques developed by Shapiro. The sound theoretical basis of these techniques is one of the major advantages of this approach. This framework also provides a new perspective on some of the hardware diagnosis techniques suggested in the literature.
6190398
Time Representation in Prolog Circuit Modelling
This paper is an examination of some issues in domain ontology and of various knowledge representation techniques for the temporal modelling of digital electronic circuits in Prolog. It should serve as an example of the advantages of such analysis, an area of relative neglect within the logic programming community.
2044368
AGATHA: An Integrated Expert System to Test and Diagnose Complex Personal Computer Boards
PA-RISC is Hewlett-Packard's (HP) reduced instruction set computer (RISC) architecture that is used in its high-performance computer systems (Mahon et al. 1986). Implementations of this architecture have produced some of the most complex processor boards that HP makes (Robinson et al. 1987; Gassman et al. 1987): They can contain as many as 8 very large scale integrated (VLSI) chips—most of them custom, from central processing units to bus controllers to floating-point pro-cessors—several high-speed random-access memory arrays, one or more high-speed buses with over 100 lines, and many other components. In large part because of this complexity, the testing of PA-RISC processor boards became a bottleneck, resulting in an undesirable backlog of undiagnosed boards, growing at a rate of 10 percent each month.
39076736
Designing Intelligent Software Agents for Auctions with Limited Information Feedback
This paper presents analytical, computational, and empirical analyses of strategies for intelligent bid formulations in online auctions. We present results related to a weighted-average ascending price auction mechanism that is designed to provide opaque feedback information to bidders and presents a challenge in formulating appropriate bids. Using limited information provided by the mechanism, we design strategies for software agents to make bids intelligently. In particular, we derive analytical results for the important characteristics of the auction, which allow estimation of the key parameters; we then use these theoretical results to design several bidding strategies. We demonstrate the validity of designed strategies using a discrete event simulation model that resembles the mechanisms used in treasury bills auctions, business-to-consumer (B2C) auctions, and auctions for environmental emission allowances. In addition, using the data generated by the simulation model, we show that intelligent strategies can provide a high probability of winning an auction without significant loss in surplus.
5097328
Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours
The problem of segmenting an image into separate regions and tracking them over time is one of the most significant problems in vision. Terzopoulos et al. (1987) proposed an approach to detect the contour regions of complex shapes, assuming a user selected initial contour not very far from the desired solution. We propose to further explore the information provided by the user's selected points and apply an optimal method to detect contours which allows a segmentation of the image. The method is based on dynamic programming (DP), and applies to a wide variety of shapes. It is exact and not iterative. We also consider a multiscale approach capable of speeding up the algorithm by a factor of 20, although at the expense of losing the guaranteed optimality characteristic. The problem of tracking and matching these contours is addressed. For tracking, the final contour obtained at one frame is sampled and used as initial points for the next frame. Then, the same DP process is applied. For matching, a novel strategy is proposed where the solution is a smooth displacement field in which unmatched regions are allowed while cross vectors are not. The algorithm is again based on DP and the optimal solution is guaranteed. We have demonstrated the algorithms on natural objects in a large spectrum of applications, including interactive segmentation and automatic tracking of the regions of interest in medical images. >
15296084
Designing online selling mechanisms: Transparency levels and prices
Sellers increasingly compete with innovative Internet-based selling mechanisms, revealing or concealing market information. Transparency strategy involves design choices by firms that influence the availability and accessibility of information about products and prices. We develop decision support models for suppliers to set prices for online mechanisms with different transparency levels. We then empirically analyze the price levels set by airlines across transparent and opaque online travel agencies. Our results suggest that airlines can increase profit by increasing price differentials or influencing OTA transparency differences. We also discuss application generality and limitations of our results.
18859582
Auctioning Vertically Integrated Online Services: Computational Approaches for Real-Time Allocation
We develop three auction-based pricing and allocation solution methods for the case where a capacity-constrained online service provider offers multiple classes of unique, one-time services with differentiated quality. Consumers desire exactly one of the many service classes offered. We call such a setting a vertically integrated online services market. Examples of these services are webcasting of special events over the Internet, provision of video-on-demand, and allocation of grid computing resources. We model the pricing and allocation decision faced by firms in such a setting as a knapsack problem with an added preference elicitation dimension. We present a variety of computational solution approaches based on adaptations of the traditional greedy heuristic for knapsack problems. The solution approaches vary in efficacy depending on whether bidders are restricted to bid in one service class or allowed to bid in multiple service classes, as well as on the overall variability of the demand. In the case bidders can bid in multiple classes but are interested in consuming only one service class, a direct application of the heuristics developed for the single service case results in a nonfair allocation. We develop a novel data structure to eliminate the unfair allocation while maintaining the original computation complexity of the simpler setting. The paper contributes by presenting a menu of auction clearing mechanisms for selling vertically integrated online services.
9910171
Semantics and CBIR: a medical imaging perspective
Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes. On the other hand, semantics in the medical domain is much better defined and there is a vast accumulation of formal knowledge representations that could be exploited to support semantic search for any specialty areas in medicine.
 In this paper, however, we will not dwell on any one particular specialty area, but rather address the question of how to support scalable semantic search across the whole of medical CBIR field: what are the advantages to take and gaps to fill, what are the key enabling technologies, and the critical success factor from an industrial point of view.
 In terms of enabling technologies, we discuss three aspects: 1. anatomical, disease, and contextual semantics, and their representations using ontologies; 2. scalable image analysis and tagging algorithms; and 3. ontological reasoning and its role in guiding and improving image analysis and retrieval.
 More specifically, for ontological representation of medical imaging semantics, we discuss the potential use of FMA, RadLex, ICD, and AIM. For scalable image analysis we present a learning-based anatomy detection and segmentation framework using distribution-free priors. It is easily adaptable to different anatomies and different imaging modalities.