Automatic Indexing from Machine Readable Abstracts of Scientific Documents
Automatic Indexing from Machine Readable Abstracts of Scientific Documents

Author: Pranas Zunde

Publisher:

Published: 1965

Total Pages: 0

ISBN-13:

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State-of-the-art of machine indexing is reported. Various proposed machine indexing methods are reviewed and evaluated. Methods for comparing machine and human indexing as well as machine indexing systems among themselves are described. Possible approaches to various problem solutions in machine indexing are indicated. The report describes the design of the Formal Autoindexing of Scientific Texts (FAST) system. Characteristics of Uniterm co- ordinate indexes are investigated and generalizations to scientific indexes made. Laws for the formation of words in the indexing language are derived and verified. The operational principles of the FAST system and test results of various system components are reported. Indexes produced by the FAST method are compared with those produced by human indexers for inter-indexer and intra- indexer consistency. A method of formal evaluation of indexes using the information theory approach is presented and applied to the FAST and conventional indexes. It is concluded that the FAST system can produce Uniterm co-ordinate indexes adequate to user's requirements better and faster than human indexers can do.

Advances in Automatic Text Summarization
Advances in Automatic Text Summarization

Author: Inderjeet Mani

Publisher: MIT Press

Published: 1999

Total Pages: 464

ISBN-13: 9780262133593

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ntil now there has been no state-of-the-art collection of themost important writings in automatic text summarization. This bookpresents the key developments in the field in an integrated frameworkand suggests future research areas. With the rapid growth of the World Wide Web and electronic information services, information is becoming available on-line at an incredible rate. One result is the oft-decried information overload. No one has time to read everything, yet we often have to make critical decisions based on what we are able to assimilate. The technology of automatic text summarization is becoming indispensable for dealing with this problem. Text summarization is the process of distilling the most important information from a source to produce an abridged version for a particular user or task. Until now there has been no state-of-the-art collection of the most important writings in automatic text summarization. This book presents the key developments in the field in an integrated framework and suggests future research areas. The book is organized into six sections: Classical Approaches, Corpus-Based Approaches, Exploiting Discourse Structure, Knowledge-Rich Approaches, Evaluation Methods, and New Summarization Problem Areas. Contributors D. A. Adams, C. Aone, R. Barzilay, E. Bloedorn, B. Boguraev, R. Brandow, C. Buckley, F. Chen, M. J. Chrzanowski, H. P. Edmundson, M. Elhadad, T. Firmin, R. P. Futrelle, J. Gorlinsky, U. Hahn, E. Hovy, D. Jang, K. Sparck Jones, G. M. Kasper, C. Kennedy, K. Kukich, J. Kupiec, B. Larsen, W. G. Lehnert, C. Lin, H. P. Luhn, I. Mani, D. Marcu, M. Maybury, K. McKeown, A. Merlino, M. Mitra, K. Mitze, M. Moens, A. H. Morris, S. H. Myaeng, M. E. Okurowski, J. Pedersen, J. J. Pollock, D. R. Radev, G. J. Rath, L. F. Rau, U. Reimer, A. Resnick, J. Robin, G. Salton, T. R. Savage, A. Singhal, G. Stein, T. Strzalkowski, S. Teufel, J. Wang, B. Wise, A. Zamora