John A. Tomlin

SemTag and seeker: bootstrapping the semantic web via automated semantic annotation

This paper describes Seeker, a platform for large-scale text analytics, and SemTag, an application written on the platform to perform automated semantic tagging of large corpora. We apply SemTag to a collection of approximately 264 million web pages, and generate approximately 434 million automatically disambiguated semantic tags, published to the web as a label bureau providing metadata regarding the 434 million annotations. To our knowledge, this is the largest scale semantic tagging effort to date.We describe the Seeker platform, discuss the architecture of the SemTag application, describe a new disambiguation algorithm specialized to support ontological disambiguation of large-scale data, evaluate the algorithm, and present our final results with information about acquiring and making use of the semantic tags. We argue that automated large scale semantic tagging of ambiguous content can bootstrap and accelerate the creation of the semantic web.

Updated triangular factors of the basis to maintain sparsity in the product form simplex method

In recent years triangular factorization of the basis has greatly enhanced the efficiency of linear programming inversion routines, leading to greater speed, accuracy and a sparser representation. This paper describes a new product form method for updating the triangular factors at each iteration of the simplex method which has proved extremely effective in reducing the rate of growth of the transformation (eta) files, thus reducing the amount of work per iteration and the frequency of re-inversion. We indicate some of the programming measures required to implement the method and give computational experience on real problems of up to 3500 rows.

A case for automated large-scale semantic annotation

Abstract This paper describes Seeker, a platform for large-scale text analytics, and SemTag, an application written on the platform to perform automated semantic tagging of large corpora. We apply SemTag to a collection of approximately 264 million web pages, and generate approximately 434 million automatically disambiguated semantic tags, published to the web as a label bureau providing metadata regarding the 434 million annotations. To our knowledge, this is the largest scale semantic tagging effort to date. We describe the Seeker platform, discuss the architecture of the SemTag application, describe a new disambiguation algorithm specialized to support ontological disambiguation of large-scale data, evaluate the algorithm, and present our final results with information about acquiring and making use of the semantic tags. We argue that automated large-scale semantic tagging of ambiguous content can bootstrap and accelerate the creation of the semantic web.

An entropy approach to unintrusive targeted advertising on the Web

Abstract This paper describes the formulation of a new model for unintrusive targeted advertising on the Web, extending the linear programming approach taken by Langheinrich et al. [M. Langheinrich, A. Nakamura, N. Abe, T. Kamba and Y. Koseki, Unintrusive customization techniques for Web advertising, in: Proc. of World Wide Web 8, 1999]. A feature of our model is that it avoids unrealistic solutions of the type which may show ads to only a too-narrow group of users. This is accomplished by using a statistically derived entropy maximization model, which incorporates a form of randomization in associating advertisements with targetable groups of users, as well as considering click-through probability. It is then shown that this nonlinear entropy model can be embedded in larger models for the purpose of optimal management of Web advertisement portfolios by agencies or brokerages.

Special ordered sets and an application to gas supply operations planning

Special Ordered Sets provide a powerful means of modeling nonconvex functions and discrete requirements, though there has been a tendency to think of them only in terms of multiple-choice zero-one programming. This paper emphasizes the origins and generality of the special ordered set concept, and describes an application in which type 2 sets are used in several forms to model both logical conditions and nonlinear functions.

An integer programming approach to a class of combinatorial problems

In this paper, we discuss the solution of a class of modified quadratic assignment problems, with particular reference to an application involving decentralization of a large organization. The main emphasis is on the use of a standard branch and bound mathematical programming system (UMPIRE) and the problem manipulations required to carry this out efficiently.

Formal optimization of some reduced linear programming problems

It is often possible (and profitable) to reduce or ‘Presolve’ linear programs. In particular, there are frequently constraints which force many of the variables to be at bound. Unfortunately, the solution found by the simplex method for such reduced models is not usually ‘formally’ optimal, in the sense that nonoptimal dual values may be present when the original problem is restored. Furthermore, the restored (full) problem is now totally degenerate, and may require many iterations to achieved formal optimality.We describe an efficient ‘Postsolve’ procedure for attaining the formal optimum solution, and give computational results.

Implementing interior point linear programming methods in the Optimization Subroutine Library

This paper discusses the implementation of interior point (barrier) methods for linear programming within the framework of the IBM Optimization Subroutine Library. This class of methods uses quite different computational kernels than the traditional simplex method. In particular, the matrices we must deal with are symmetric and, although still sparse, are considerably denser than those assumed in simplex implementations. Severe rank deficiency must also be accommodated, making it difficult to use off-the-shelf library routines. These features have particular implications for the exploitation of the newer IBM machine architectural features. In particular, interior methods can benefit greatly from use of vector architectures on the IBM 3090™ series computers and “super-scalar“ processing on the RISC System/6000™ series.