Engineering topics

Silvester, June P.

Publications and source records attributed to Silvester, June P..

6 records

NASA NTRS1997

Computer Supported Indexing: A History and Evaluation of NASA's MAI System

Computer supported or machine aided indexing (MAI) can be categorized in multiple ways. The system used by the National Aeronautics and Space Administration's (NASA's) Center for AeroSpace Information (CASI) is described as semantic and computational. It's based on the co-occurrence of domain-specific terminology in parts of a sentence, and the probability that an indexer will assign a particular index term when a given word or phrase is encountered in text. The NASA CASI system is run on demand by the indexer and responds in 3 to 9 seconds with a list of suggested, authorized terms. The system was originally based on a syntactic system used in the late 1970's by the Defense Technical Information Center (DTIC). The NASA mainframe-supported system consists of three components: two programs and a knowledge base (KB). The evolution of the system is described and flow charts illustrate the MAI procedures. Tests used to evaluate NASA's MAI system were limited to those that would not slow production. A very early test indicated that MAI saved about 3 minutes and provided several additional terms for each document indexed. It also was determined that time and other resources spent in careful construction of the KB pay off with high-quality output and indexer acceptance of MAI results.

Silvester, June P.↗

NASA NTRS1997

Computer Supported Indexing: A History and Evaluation of NASA's MAI System

Computer supported indexing systems may be categorized in several ways. One classification scheme refers to them as statistical, syntactic, semantic or knowledge-based. While a system may emphasize one of these aspects, most systems actually combine two or more of these mechanisms to maximize system efficiency. Statistical systems can be based on counts of words or word stems, statistical association, and correlation techniques that assign weights to word locations or provide lexical disambiguation, calculations regarding the likelihood of word co-occurrences, clustering of word stems and transformations, or any other computational method used to identify pertinent terms. If words are counted, the ones of median frequency become candidate index terms. Syntactical systems stress grammar and identify parts of speech. Concepts found in designated grammatical combinations, such as noun phrases, generate the suggested terms. Semantic systems are concerned with the context sensitivity of words in text. The primary goal of this type of indexing is to identify without regard to syntax the subject matter and the context-bearing words in the text being indexed. Knowledge-based systems provide a conceptual network that goes past thesaurus or equivalent relationships to knowing (e.g., in the National Library of Medicine (NLM) system) that because the tibia is part of the leg, a document relating to injuries to the tibia should he indexed to LEG INJURIES, not the broader MeSH term INJURIES, or knowing that the term FEMALE should automatically be added when the term PREGNANCY is assigned, and also that the indexer should be prompted to add either HUMAN or ANIMAL. Another way of categorizing indexing systems is to identify them as producing either assigned- or derived-term indexes.

Silvester, June P.↗

NASA NTRS1994

Machine-aided indexing at NASA

This report describes the NASA Lexical Dictionary (NLD), a machine-aided indexing system used online at the National Aeronautics and Space Administration's Center for AeroSpace Information (CASI). This system automatically suggests a set of candidate terms from NASA's controlled vocabulary for any designated natural language text input. The system is comprised of a text processor that is based on the computational, nonsyntactic analysis of input text and an extensive knowledge base that serves to recognize and translate text-extracted concepts. The functions of the various NLD system components are described in detail, and production and quality benefits resulting from the implementation of machine-aided indexing at CASI are discussed.

Silvester, June P.↗

NASA NTRS1993

NASA's online machine aided indexing system

This report describes the NASA Lexical Dictionary, a machine aided indexing system used online at the National Aeronautics and Space Administration's Center for Aerospace Information (CASI). This system is comprised of a text processor that is based on the computational, non-syntactic analysis of input text, and an extensive 'knowledge base' that serves to recognize and translate text-extracted concepts. The structure and function of the various NLD system components are described in detail. Methods used for the development of the knowledge base are discussed. Particular attention is given to a statistically-based text analysis program that provides the knowledge base developer with a list of concept-specific phrases extracted from large textual corpora. Production and quality benefits resulting from the integration of machine aided indexing at CASI are discussed along with a number of secondary applications of NLD-derived systems including on-line spell checking and machine aided lexicography.

Silvester, June P.↗

NASA NTRS1993

Machine aided indexing from natural language text

The NASA Lexical Dictionary (NLD) Machine Aided Indexing (MAI) system was designed to (1) reuse the indexing of the Defense Technical Information Center (DTIC); (2) reuse the indexing of the Department of Energy (DOE); and (3) reduce the time required for original indexing. This was done by automatically generating appropriate NASA thesaurus terms from either the other agency's index terms, or, for original indexing, from document titles and abstracts. The NASA STI Program staff devised two different ways to generate thesaurus terms from text. The first group of programs identified noun phrases by a parsing method that allowed for conjunctions and certain prepositions, on the assumption that indexable concepts are found in such phrases. Results were not always satisfactory, and it was noted that indexable concepts often occurred outside of noun phrases. The first method also proved to be too slow for the ultimate goal of interactive (online) MAI. The second group of programs used the knowledge base (KB), word proximity, and frequency of word and phrase occurrence to identify indexable concepts. Both methods are described and illustrated. Online MAI has been achieved, as well as several spinoff benefits, which are also described.

Silvester, June P.↗

NASA NTRS1993

An operational system for subject switching between controlled vocabularies

The NASA system of automatically converting sets of terms assigned by Department of Defense indexers to sets of NASA's authorized terms is described. This little-touted system, which has been operating successfully since 1983, matches concepts, rather than words. Subject Switching uses a translation table, known as the Lexical Dictionary, accessed by a program that determines which rules to follow in making the transition from DTIC's to NASA's authorized terms. The authors describe the four phases of development of Subject Switching, changes that have been made, evaluating the system, and benefits. Benefits to NASA include saving indexers' time, the addition of access points for documents indexed, the utilization of other government indexing, and a contribution towards the now-operational NASA, online, interactive, machine aided indexing.

Silvester, June P.↗