Forty Years of Text Indexing

International audienceThis paper reviews the first 40 years in the life of textual inverted indexes, their many incarnations, and their applications. The paper is non-technical and assumes some familiarity with the structures and constructions discussed. It is not meant to be exhaustive. It is meant to be a tribute to a ubiquitous tool of string matching — the suffix tree and its variants — and one of the most persistent subjects of study in the theory of algorithms

Education for Librarianship in the Next Century

published or submitted for publicatio

Some Issues Raised By Alaska’s Recording Act

A novel method to find the orientation and position of a triaxial accelerometer mounted on a six degrees-of-freedom industrial robot is proposed and evaluated on experimental data. The method consists of two consecutive steps, where the first is to estimate the orientation of the accelerometer from static experiments. In the second step the accelerometer position relative to the robot base is identified using accelerometer readings when the accelerometer moves in a circular path and where the accelerometer orientation is kept constant in a path fixed coordinate system. Once the accelerometer position and orientation are identified it is possible to use the accelerometer in robot model parameter identification and in advanced control solutions. Compared to previous methods, the accelerometer position estimation is completely new, whereas the orientation is found using an analytical solution to the optimisation problem. Previous methods use a parameterisation where the optimisation uses an iterative solver.LINK-SI

Legal Information and the Development of American Law: Writings on the Form and Structure of the Published Law

Robert C. Berring\u27s writings about the impacts of electronic databases, the Internet, and other communications technologies on legal research and practice are an essential part of a larger literature that explores the ways in which the forms and structures of published legal information have influenced how American lawyers think about the law. This paper reviews Berring\u27s writings, along with those of other writers concerned with these questions, focusing on the implications of Berring\u27s idea that in the late nineteenth century American legal publishers created a conceptual universe of thinkable thoughts through which U.S. lawyers came to view the law. It concludes that, spurred by Berring and others, the literature of legal information has become far reaching in scope and interdisciplinary in approach, while the themes struck in Berring\u27s work continue to inform the scholarship of newer writers

Keywords given by authors of scientific articles in database descriptors

This paper analyses the keywords given by authors of scientific articles and the descriptors assigned to the articles in order to ascertain the presence of the keywords in the descriptors. 640 INSPEC, CAB abstracts, ISTA and LISA database records were consulted. After detailed comparisons it was found that keywords provided by authors have an important presence in the database descriptors studied, since nearly 25% of all the keywords appeared in exactly the same form as descriptors, with another 21% while normalized, are still detected in the descriptors. This means that almost 46% of keywords appear in the descriptors, either as such or after normalization. Elsewhere, three distinct indexing policies appear, one represented by INSPEC and LISA (indexers seem to have freedom to assign the descriptors they deem necessary); another is represented by CAB (no record has fewer than four descriptors and, in general, a large number of descriptors is employed; in contrast, in ISTA, a certain institutional code towards economy in indexing, since 84% of records contain only four descriptors

Abstracts and Abstracting in Knowledge Discovery

published or submitted for publicatio

Indexing and Inflation

Much of the opposition to indexation as a means of adapting to on going inflation arises from the view that indexation is itself inflationary. This paper examines the basis for that view in a simple macroeconomic model in which budget deficits are in part financed through the printing of money. It is shown that all aspects of indexing -- wage indexation, bond indexation, and tax indexation -- tend to increase the impact on the price level of any inflationary shock. However, this association between indexation and inflation is in large part a consequence of the monetary and fiscal policies being followed by the government. Evidence from a cross-section of forty countries on the effects of indexation on the inflationary impact of the oil price shock of 1974 suggests that indexation did not in general increase the inflationary impact of the oil shock. However, the impact of the oil shock was significantly stronger in those countries that had adopted bond indexation.

Special Libraries, December 1954

Volume 45, Issue 10https://scholarworks.sjsu.edu/sla_sl_1954/1009/thumbnail.jp

The Potential of Learned Index Structures for Index Compression

Inverted indexes are vital in providing fast key-word-based search. For every term in the document collection, a list of identifiers of documents in which the term appears is stored, along with auxiliary information such as term frequency, and position offsets. While very effective, inverted indexes have large memory requirements for web-sized collections. Recently, the concept of learned index structures was introduced, where machine learned models replace common index structures such as B-tree-indexes, hash-indexes, and bloom-filters. These learned index structures require less memory, and can be computationally much faster than their traditional counterparts. In this paper, we consider whether such models may be applied to conjunctive Boolean querying. First, we investigate how a learned model can replace document postings of an inverted index, and then evaluate the compromises such an approach might have. Second, we evaluate the potential gains that can be achieved in terms of memory requirements. Our work shows that learned models have great potential in inverted indexing, and this direction seems to be a promising area for future research.Comment: Will appear in the proceedings of ADCS'1