14282973
Closing the Gap: Learning-Based Information Extraction Rivaling Knowledge-Engineering Methods
In this paper, we present a learning approach to the scenario template task of information extraction, where information filling one template could come from multiple sentences. When tested on the MUC-4 task, our learning approach achieves accuracy competitive to the best of the MUC-4 systems, which were all built with manually engineered rules. Our analysis reveals that our use of full parsing and state-of-the-art learning algorithms have contributed to the good performance. To our knowledge, this is the first research to have demonstrated that a learning approach to the full-scale information extraction task could achieve performance rivaling that of the knowledge engineering approach.
16022713
Query based event extraction along a timeline
In this paper, we present a framework and a system that extracts events relevant to a query from a collection C of documents, and places such events along a timeline. Each event is represented by a sentence extracted from C, based on the assumption that "important" events are widely cited in many documents for a period of time within which these events are of interest. In our experiments, we used queries that are event types ("earthquake") and person names (e.g. "George Bush"). Evaluation was performed using G8 leader names as queries: comparison made by human evaluators between manually and system generated timelines showed that although manually generated timelines are on average more preferable, system generated timelines are sometimes judged to be better than manually constructed ones.
14857474
Optimal design and use of retry in fault-tolerant computer systems
In this paper, a new method is presented for (i) determining an optimal retry policy and (ii) using retry for fault characterization, which is defined as classification of the fault type and determination of fault durations. First, an optimal retry policy is derived for a given fault characteristic, which determines the maximum allowable retry durations so as to minimize the total task completion time. Then, the combined fault characterization and retry decision, in which the characteristic of a fault is estimated simultaneously with the determination of the optimal retry policy, are carried out. Two solution approaches are developed: one is based on point estimation and the other on Bayes sequential decision analysis.
Numerical examples are presented in which all the durations associated with faults (i.e., active, benign, and interfailure durations) have monotone hazard rate functions (e.g., exponential Weibull and gamma distributions). These are standard distributions commonly used for modeling and analyses of faults.
5961676
Total Data Quality Management: The Case of IRI
Abstract Implementing a Total Data Quality Management (TDQM) program is not a trivial undertaking. Two key steps are (1) to clearly define what an organization means by data quality and (2) to develop metrics that measure data quality dimensions and that are linked to the organization’s goals and objectives. This paper presents the case of Information Resources, Inc., which exemplifies how a company can develop a viable TDQM program.
9259468
Classification of Multiple Cancer Types by Multicategory Support Vector Machines Using Gene Expression Data
MOTIVATION
High-density DNA microarray measures the activities of several thousand genes simultaneously and the gene expression profiles have been used for the cancer classification recently. This new approach promises to give better therapeutic measurements to cancer patients by diagnosing cancer types with improved accuracy. The Support Vector Machine (SVM) is one of the classification methods successfully applied to the cancer diagnosis problems. However, its optimal extension to more than two classes was not obvious, which might impose limitations in its application to multiple tumor types. We briefly introduce the Multicategory SVM, which is a recently proposed extension of the binary SVM, and apply it to multiclass cancer diagnosis problems.


RESULTS
Its applicability is demonstrated on the leukemia data (Golub et al., 1999) and the small round blue cell tumors of childhood data (Khan et al., 2001). Comparable classification accuracy shown in the applications and its flexibility render the MSVM a viable alternative to other classification methods.


SUPPLEMENTARY INFORMATION
http://www.stat.ohio-state.edu/~yklee/msvm.htm
17546848
Analysis of Fuzzy Operators for High Quality Information Retrieval
Kim, M.H., J.H. Lee and Y.J. Lee, Analysis of fuzzy operators for high quality information retrieval. Information Processing Letters 46 (1993) 251-256. It has been argued that the conventional fuzzy set model based on the MIN and MAX operators is not appropriate for a model of information retrieval systems due to the properties of the MIN and MAX operators adverse to retrieval effectiveness. In this paper we investigate the behavioral aspects of various fuzzy operators and address the properties which are important in achieving high quality document rankings. We then present the fuzzy set model based on positively compensatory operators, which provides higher retrieval effectiveness than the conventional fuzzy set model. It is also described that the behavior of the proposed fuzzy set model almost coincides with that of the extended boolean model.
12566781
Web-Based Simulation with Server Application Approach under Distributed Environment