Abstracts and Abstracting in Knowledge Discovery

published or submitted for publicatio

Special Libraries, December 1970

Volume 61, Issue 10https://scholarworks.sjsu.edu/sla_sl_1970/1009/thumbnail.jp

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

An experiment with ontology mapping using concept similarity

This paper describes a system for automatically mapping between concepts in different ontologies. The motivation for the research stems from the Diogene project, in which the project's own ontology covering the ICT domain is mapped to external ontologies, in order that their associated content can automatically be included in the Diogene system. An approach involving measuring the similarity of concepts is introduced, in which standard Information Retrieval indexing techniques are applied to concept descriptions. A matrix representing the similarity of concepts in two ontologies is generated, and a mapping is performed based on two parameters: the domain coverage of the ontologies, and their levels of granularity. Finally, some initial experimentation is presented which suggests that our approach meets the project's unique set of requirements

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Template Mining for Information Extraction from Digital Documents

published or submitted for publicatio

Representation and use of chemistry in the global electronic age.

We present an overview of the current state of public semantic chemistry and propose new approaches at a strategic and a detailed level. We show by example how a model for a Chemical Semantic Web can be constructed using machine-processed data and information from journal articles.This manuscript addresses questions of robotic access to data and its automatic re-use, including the role of Open Access archival of data. This is a pre-refereed preprint allowed by the publisher's (Royal Soc. Chemistry) Green policy. The author's preferred manuscript is an HTML hyperdocument with ca. 20 links to images, some of which are JPEgs and some of which are SVG (scalable vector graphics) including animations. There are also links to molecules in CML, for which the Jmol viewer is recommended. We susgeest that readers who wish to see the full glory of the manuscript, download the Zipped version and unpack on their machine. We also supply a PDF and DOC (Word) version which obviously cannot show the animations, but which may be the best palce to start, particularly for those more interested in the text

Evaluation of controlled vocabularies by inter-indexer consistency

Introduction. Several controlled vocabularies are used for indexing three journal articles to check if with a list of descriptors are achieved better or equals of consistency rates that with a standard thesaurus and augmented thesaurus. Method. A set of terminology of Library and Information Science was used to build a list of descriptors with equivalence relations (USE and UF), a standard thesaurus and a augmented thesaurus (all the descriptors have scope notes). Subsequently, three articles were indexed by selected indexers who had varying degrees of experience – on the one hand Library and Information Science students and on the other, professionals from various documentation centres. Hooper’s measure to find the consistency between pairs of novice indexers and experts has been applied. Analysis. Data were tabulated and analysed systematically according pairs of novice indexers and experts has been applied. Results. The tool with the best results is the list of descriptors (39.5% consistency), followed by the augmented thesaurus (29.8%) and, with an almost identical value, the standard thesaurus (27.5%). Conclusion. It is concluded that the list of descriptors in both groups returns better indexing consistency but we need more research