-
Zeng, L.: Automatic indexing for Chinese text : problems and progress (1992)
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-
Silvester, J.P.: Computer supported indexing : a history and evaluation of NASA's MAI system (1998)
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-
Hlava, M.M.K.: Machine-Aided Indexing (MAI) in a multilingual environemt (1992)
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- Abstract
- The Machine-Aided Indexing (MAI) program, developed by Access Innovations, Inc., is a semantic based, Boolean statement, rule interpreting application designed to operate in a multilingual environment. Use of MAI across several languages with controlled vocabularies for each language provides a consistency in indexing not available through any other mechanism
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Garfield, E.: ¬The relationship between mechanical indexing, structural linguistics and information retrieval (1992)
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- Abstract
- It is possible to locate over 60% of indexing terms used in the Current List of Medical Literature by analysing the titles of the articles. Citation indexes contain 'noise' and lack many pertinent citations. Mechanical indexing or analysis of text must begin with some linguistic technique. Discusses Harris' methods of structural linguistics, discourse analysis and transformational analysis. Provides 3 examples with references, abstracts and index entries
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Alexander, M.: Retrieving digital data with fuzzy matching (1996)
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- Abstract
- Briefly describes the Excalibur EFS system which makes use of adaptive pattern recognition technology as an aid to automatic indexing and how it is being tested at the British Library for the indexing and retrieval of scanned images from the library's holdings. Notes how Excalibur EFS can support a wide degree of fuzzy searching, compensate for the errors produced by OCR conversion of scanned images, reduce the costs of indexing, and require far less storage space than more traditional indexes
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Leung, C.-H.; Kan, W.-K.: ¬A statistical learning approach to automatic indexing of controlled index terms (1997)
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- Abstract
- A statistical learning approach to assigning controlled index terms is presented. In this approach, there are two processes: (1) the learning process and (2) the indexing process. The learning process constructs a relationship between an index term and the words relevant and irrelevant to it, based on the positive training set and negative training set, and those not indexed by it, respectively. The indexing process determines whether an index term is assigned to a certain document, based on the relationship constructed by the learning process, and the text found in the document. Furthermore, a learning feedback technique is introduced. This technique used in the learning process modifies the relationship between an index term and its relevant and irrelevant words to improve the learning performance and, thus, the indexing performance. Experimental results have shown that the statistical learning approach and the learning feedback technique are practical means to automatic indexing of controlled index terms
-
MacDougall, S.: Rethinking indexing : the impact of the Internet (1996)
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- Abstract
- Considers the challenge to professional indexers posed by the Internet. Indexing and searching on the Internet appears to have a retrograde step, as well developed and efficient information retrieval techniques have been replaced by cruder techniques, involving automatic keyword indexing and frequency ranking, leading to large retrieval sets and low precision. This is made worse by the apparent acceptance of this poor perfromance by Internet users and the feeling, on the part of indexers, that they are being bypassed by the producers of these hyperlinked menus and search engines. Key issues are: how far 'human' indexing will still be required in the Internet environment; how indexing techniques will have to change to stay relevant; and the future role of indexers. The challenge facing indexers is to adapt their skills to suit the online environment and to convince publishers of the need for efficient indexes on the Internet
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Hersh, W.R.; Hickam, D.H.: ¬A comparison of two methods for indexing and retrieval from a full-text medical database (1992)
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- Abstract
- Reports results of a study of 2 information retrieval systems on a 2.000 document full text medical database. The first system, SAPHIRE, features concept based automatic indexing and statistical retrieval techniques, while the second system, SWORD, features traditional word based Boolean techniques, 16 medical students at Oregon Health Sciences Univ. each performed 10 searches and their results, recorded in terms of recall and precision, showed nearly equal performance for both systems. SAPHIRE was also compared with a version of SWORD modified to use automatic indexing and ranked retrieval. Using batch input of queries, the latter method performed slightly better
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Silvester, J.P.; Genuardi, M.T.; Klingbiel, P.H.: Machine-aided indexing at NASA (1994)
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- Abstract
- Describes the NASA Lexical Dictionary (NLD), a machine aided indexing system used online at the NASA 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
-
Hlava, M.M.K.: Machine aided indexing (MAI) in a multilingual environment (1993)
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- Abstract
- The machine aided indexing (MAI) software devloped by Access Innovations, Inc., is a semantic based, Boolean statement, rule interpreting application with 3 modules: the MA engine which accepts input files, matches terms in the knowledge base, interprets rules, and outputs a text file with suggested indexing terms; a rule building application allowing each Boolean style rule in the knowledge base to be created or modifies; and a statistical computation module which analyzes performance of the MA software against text manually indexed by professional human indexers. The MA software can be applied across multiple languages and can be used where the text to be searched is in one language and the indexes to be output are in another
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Smith, P.J.; Normore, L.F.; Denning, R.; Johnson, W.P.: Computerized tools to support document analysis (1994)
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- Source
- Challenges in indexing electronic text and images. Ed.: R. Fidel et al
-
Koryconski, C.; Newell, A.F.: Natural-language processing and automatic indexing (1990)
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- Abstract
- The task of producing satisfactory indexes by automatic means has been tackled on two fronts: by statistical analysis of text and by attempting content analysis of the text in much the same way as a human indexer does. Though statistical techniques have a lot to offer for free-text database systems, neither method has had much success with back-of-the-book indexing. This review examines some problems associated with the application of natural-language processing techniques to book texts. - Vgl. auch die Erwiderung von K.P. Jones
-
Schuegraf, E.J.; Bommel, M.F.van: ¬An automatic document indexing system based on cooperating expert systems : design and development (1993)
0.02
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- Abstract
- Discusses the design of an automatic indexing system based on two cooperating expert systems and the investigation related to its development. The design combines statistical and artificial intelligence techniques. Examines choice of content indicators, the effect of stemming and the identification of characteristic vocabularies for given subject areas. Presents experimental results. Discusses the application of machine learning algorithms to the identification of vocabularies
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Alexander, M.: Automatic indexing of document images using Excalibur EFS (1995)
0.02
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- Abstract
- Discusses research into the application of adaptive pattern recognition technology to enable effective retrieval from scanned document images. Describes application at the British Library of Excalibur EFS software which uses adaptive pattern recognition technology to provide access to digital information in its native forms, fuzzy searching retrieval and automatic indexing capabilities. It was used to make specialist printed catalogues and indexes accessible on computer via content based indexes
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Hlava, M.M.K.; Hainebach, R.: Machine aided indexing : European Parliament study and results (1996)
0.02
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- Abstract
- Reports on a pilot study of the application of Access Innovations' machine aided indexing (MAI) system on the European Parliament's full text materials. Describes how the knowledge base used by the MAI software is created, and gives an evaluation of the system
-
Mars, N.J.I.: ¬The management of scientific information, or, how to cope with the flood (1996)
0.02
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- Abstract
- Research in the Knowledge-Based Systems Group of the University of Twente in the Netherlands is aimed at reducing information overload. One approach is to support indexing by the traditional method of assigning content descriptions to find documents. A second way is to use a computer program to determine what the document says without descriptors. Discusses automated indexing and direct access to information
-
Dow Jones unveils knowledge indexing system (1997)
0.02
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- Abstract
- Dow Jones Interactive Publishing has developed a sophisticated automatic knowledge indexing system that will allow searchers of the Dow Jones News / Retrieval service to get highly targeted results from a search in the service's Publications Library. Instead of relying on a thesaurus of company names, the new system uses a combination of that basic algorithm plus unique rules based on the editorial styles of individual publications in the Library. Dow Jones have also announced its acceptance of the definitions of 'selected full text' and 'full text' from Bibliodata's Fulltext Sources Online directory
-
Fox, C.: Lexical analysis and stoplists (1992)
0.02
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- Abstract
- Lexical analysis is a fundamental operation in both query processing and automatic indexing, and filtering stoplist words is an important step in the automatic indexing process. Presents basic algorithms and data structures for lexical analysis, and shows how stoplist word removal can be efficiently incorporated into lexical analysis
-
Ferber, R.: Automated indexing with thesaurus descriptors : a co-occurence based approach to multilingual retrieval (1997)
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- Abstract
- Indexing documents with descriptors from a multilingual thesaurus is an approach to multilingual information retrieval. However, manual indexing is expensive. Automazed indexing methods in general use terms found in the document. Thesaurus descriptors are complex terms that are often not used in documents or have specific meanings within the thesaurus; therefore most weighting schemes of automated indexing methods are not suited to select thesaurus descriptors. In this paper a linear associative system is described that uses similarity values extracted from a large corpus of manually indexed documents to construct a rank ordering of the descriptors for a given document title. The system is adaptive and has to be tuned with a training sample of records for the specific task. The system was tested on a corpus of some 80.000 bibliographic records. The results show a high variability with changing parameter values. This indicated that it is very important to empirically adapt the model to the specific situation it is used in. The overall median of the manually assigned descriptors in the automatically generated ranked list of all 3.631 descriptors is 14 for the set used to adapt the system and 11 for a test set not used in the optimization process. This result shows that the optimization is not a fitting to a specific training set but a real adaptation of the model to the setting
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Driscoll, J.R.; Rajala, D.A.; Shaffer, W.H.: ¬The operation and performance of an artificially intelligent keywording system (1991)
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- Abstract
- Presents a new approach to text analysis for automating the key phrase indexing process, using artificial intelligence techniques. This mimics the behaviour of human experts by using a rule base consisting of insertion and deletion rules generated by subject-matter experts. The insertion rules are based on the idea that some phrases found in a text imply or trigger other phrases. The deletion rules apply to semantically ambiguous phrases where text presence alone does not determine appropriateness as a key phrase. The insertion and deletion rules are used to transform a list of found phrases to a list of key phrases for indexing a document. Statistical data are provided to demonstrate the performance of this expert rule based system
