35854986
News Headline Generation based on Linguistic Methods
36952841
Textual CBR for Incident Report Retrieval
Incident Management Systems can play a crucial role in helping to reduce the number of workplace accidents by providing support for incident analysis. In particular, the retrieval of relevant similar incident reports can help safety personnel to identify factors and patterns that have contributed or might potentially contribute to accidents. Incident Report Retrieval is a relatively new research topic in the field of Accident Reporting and Analysis, and we are interested in developing intelligent computational support for retrieving incident information that leverages both the featural and textual components of incident reports. This paper describes InRet-T, an Incident Report Retrieval system that incorporates approaches from textual case-based reasoning to integrate both featural and textual aspects in retrieving civil aviation incident reports. It also provides a preliminary evaluation of InRet-T that offers some insight into the use of textual CBR approaches to incident analysis.
1431727
Combining Flexibility and Scalability in a Peer-to-Peer Publish/Subscribe System
The content-based publish/subscribe model has been adopted by many services to deliver data between distributed users based on application-specific semantics. Two key issues in such systems, the semantic expressiveness of content matching and the scalability of the matching mechanism, are often found to be in conflict due to the complexity associated with content matching. In this paper, we present a novel content-based publish/subscribe architecture based on peer-to-peer matching trees. The system achieves scalability by partitioning the responsibility of event matching to self-organized peers while allowing customizable matching functionalities. Experimental results using a variety of real world datasets demonstrate the scalability and flexibility of the system.
8792310
xFS: a wide area mass storage file system
The current generation of file systems are inadequate in facing the new technological challenges of wide area networks and massive storage. xFS is a prototype file system we are developing to explore the issues brought about by these technological advances. xFS adapts many of the techniques used in the field of high performance multiprocessor design. It organizes hosts into a hierarchical structure so locality within clusters of workstations can be better exploited. By using an invalidation-based write back cache coherence protocol, xFS minimizes network usage. It exploits the file system naming structure to reduce cache coherence state. xFS also integrates different storage technologies in a uniform manner. Due to its intelligent use of local hosts and local storage, we expect xFS to achieve better performance and availability than current generation network file systems run in the wide area.<<ETX>>
1318806
Brushwood: Distributed Trees in Peer-to-Peer Systems
There is an increasing demand for locality-preserving distribution of complex data structures in peer-to-peer systems. Current systems either do not preserve object locality or suffer from imbalances in data distribution, routing state, and/or query processing costs. In this position paper, we take a systematic approach that enables the deployment of searchable tree structures in p2p environments. We achieve distributed tree traversal with efficient routing distance and routing state. We show how to implement several p2p applications using distributed tree structures.
1050293
Understanding captions in biomedical publications
From the standpoint of the automated extraction of scientific knowledge, an important but little-studied part of scientific publications are the figures and accompanying captions. Captions are dense in information, but also contain many extra-grammatical constructs, making them awkward to process with standard information extraction methods. We propose a scheme for "understanding" captions in biomedical publications by extracting and classifying "image pointers" (references to the accompanying image). We evaluate a number of automated methods for this task, including hand-coded methods, methods based on existing learning techniques, and methods based on novel learning techniques. The best of these methods leads to a usefully accurate tool for caption-understanding, with both recall and precision in excess of 94% on the most important single class in a combined extraction/classification task.
8135553
Highly secure and efficient routing
In this paper, we consider the problem of routing in an adversarial environment, where a sophisticated adversary has penetrated arbitrary parts of the routing infrastructure and attempts to disrupt routing. We present protocols that are able to route packets as long as at least one nonfaulty path exists between the source and the destination. These protocols have low communication overhead, low processing requirements, low incremental cost, and fast fault detection. We also present extensions to the protocols that penalize adversarial routers by blocking their traffic.