IBM

About: IBM is a company organization based out in Armonk, New York, United States. It is known for research contribution in the topics: Layer (electronics) & Signal. The organization has 134567 authors who have published 253905 publications receiving 7458795 citations. The organization is also known as: International Business Machines Corporation & Big Blue.

Automated learning of decision rules for text categorization

Abstract: We describe the results of extensive experiments using optimized rule-based induction methods on large document collections. The goal of these methods is to discover automatically classification patterns that can be used for general document categorization or personalized filtering of free text. Previous reports indicate that human-engineered rule-based systems, requiring many man-years of developmental efforts, have been successfully built to “read” documents and assign topics to them. We show that machine-generated decision rules appear comparable to human performance, while using the identical rule-based representation. In comparison with other machine-learning techniques, results on a key benchmark from the Reuters collection show a large gain in performance, from a previously reported 67% recall/precision breakeven point to 80.5%. In the context of a very high-dimensional feature space, several methodological alternatives are examined, including universal versus local dictionaries, and binary versus frequency-related features.

Reasoning about Infinite Computations

Abstract: We investigate extensions of temporal logic by connectives defined by finite automata on infinite words. We consider three different logics, corresponding to three different types of acceptance conditions (finite, looping, and repeating) for the automata. It turns out, however that these logics all have the same expressive power and that their decision problems are all PSPACE-complete. We also investigate connectives defined by alternating automata and show that they do not increase the expressive power of the logic or the complexity of the decision problem.

Apparatus, system, and method for autonomic control of grid system resources

Abstract: An apparatus, system, and method are disclosed for autonomic management of data operations and performance resources on a grid computing system. An autonomic management apparatus includes a monitor module, a policy module, and a regulation module. The monitor module is configured to monitor the grid computing system for a trigger event. The policy module is configured to access one of a plurality of system policies. Each of the plurality of system policies corresponds to an operational control parameter of a system resource of the grid computing system. The regulation module is configured to autonomically regulate the system resource in response to a recognized trigger event according to one of the plurality of system policies. The trigger event may be a prediction trigger event, an initiation trigger event, a regulation trigger event, or a termination trigger event.

Apparatus, system, and method for database provisioning

Abstract: An apparatus, system, and method are disclosed for provisioning database resource within a grid database system. The federation apparatus includes an analysis module and a provision module. The analysis module analyzes a data query stream from an application to a database instance and determines if the data query stream exhibits a predetermined performance attribute. The provision module provisions a database resource in response to a determination that the data query stream exhibits the predetermined performance attribute. The provisioned database resource may be a database instance or a cache. The provisioning of the new database resource advantageously is substantially transparent to a client on the database system.