In order to improve the automatic production of meta-information in the abstracting field, an essential starting point is the exposition of the current state of the art. At the level of content, three significantly different types of procedure stand out, depending on the document structure in question: extracting, rhetorical summarizing and cognitive summarizing. In addition, reticular and graphic models of information representation, much more appropriate to digital environments, offer a complementary method. In all cases, prior definition of the domain, with its specific documents and actors, is needed. However, the low quality of the product derived from full automation (extract and summaries), above all lacking in coherence, led us to the concept of partial automation, a hybrid man-machine methodology that, at least for the time being, seems to be the best solution for the abstract and abstracting problem.
[1] S.L. Vellucci , Metadata , Annual Review of Information Science and Technology (ARIST)33 (1998) 187-222 .
2.
[2] A. Chilvers and J. Feather , The management of digital data: a metadata approach , The Electronic Library16(6) (1998) 365-371 .
3.
[3] R. Heery , A. Powell and M. Day , Metadata, Library & Information Briefings, Vol. 75 ( South Bank University, London , 1997).
4.
[4] H.P. Luhn , The automatic creation of literature abstracts , IBM Journal Research and Development2(2) (1958) 159-165 .
5.
[5] B. Mathis and J. Rush , Abstracting. In: E. Dym (ed.), Subject and Information Analysis ( Marcel Dekker, New York , 1985)..
6.
[6] E. Liddy , Natural language processing. In: P. Atherton and E. H. Johnson (eds), Visualizing Subject Acces for 21st Century Information Resources ( University of Illinois, Urbana-Champaign, IL , 1998).
7.
[7] J. Allen , Natural Language Understanding ( Benjamin Cumming , 1995).
8.
[8] M.F. Moens , Automatic Indexing and Abstracting of Document Texts ( Kluwer Academic, Boston, MA , 2000).
9.
[9] K. SparckJones, Automatic summarising: factors and directions. In: I. Mani and M. Maybury (eds), Advances in Automatic Text Summarization ( MIT Press, Cambridge, MA , 1998).
10.
[10] G. Salton , Automatic Text Processing ( Addison-Wesley, New York , 1989).
11.
[11] C.J. Armstrong and A. Wheatley , A Survey of the Content and Characteristics of Electronic Abstracts ( Library Information Technology Centre, London , 1997).
12.
[12] A. Gilchrist , Who is responsible for information quality in the information society? In: 5th Jornades Catalanes de Documentacio ( Barcelona , 1995).
13.
[13] J.L. Milstead , Thesauri in a full text world. In: P. Atherton and E.H. Johnson (eds), Visualizing Subject Access for 21st Century Information Resources ( University of Illinois, Urbana-Champaign , 1998).
14.
[14] J. Qin and K. Wesley , Web indexing with meta fields: a survey of web objects in polymer chemistry , Information Technology and Libraries7(3) (1998) 149-156 .
15.
[15] L. Dempsey and R. Heery , Metadata: a current view of practice and issues , Journal of Documentation54(2) (1998) 145-172 .
16.
[16] A. Wheatley and C.J. Armstrong , Metadata, recall, and abstracts: can abstracts ever be reliable indicators of document value?Aslib Proceedings49(8) (1997) 206-213 .
17.
[17] J.G. Kircz , Rhetorical structure of scientific articles: the case for argumentational analysis in information retrieval , Journal of Documentation47(4) (1991) 354-372 .
18.
[18] H. Borko and Ch. Bernier , Abstracting Concepts and Methods ( Academic Press, New York , 1975).
19.
[19] C. Paice , Constructing literature abstracts by computer: techniques and prospects , Information Processing and Management26(1) (1990) 171-186 .
20.
[20] J. Kupiec , J. Pedersen and F. Chen , A trainable document summarizer . In: E.A. Fox , P. Ingwersen and R. Fidel (eds), Proceedings of the 18th ACM-SIGIR Conference on Research and Development in Information Retrieval (Seattle, WA, 1995).
21.
[21] S. Teufel and M. Moens , Sentence extraction as a classification task . In: I. Mani and M. Maybury (eds), Intelligent Scalable Text Summarization . Proceedings of a Workshop Sponsored by the Association for Computational Linguistics (Madrid, 1997).
22.
[22] IBM Corporation, Advanced Systems Development, ACSI-Matic Auto-Abstracting Project, Final report 1-3 (1960-1961).
23.
[23] H.P. Edmundson , New methods in automatic extracting , Journal of the Association of Computing Machinery16(2) (1969) 264-285 .
24.
[24] H.P. Edmundson , V.A. Oswald and R. E. Wyllys , Automatic Indexing and Abstracting of the Contents of Documents ( Planning Research Corporation, Los Angeles, CA , 1959).
25.
[25] J.E. Rush , R. Salvador and A. Zamora , Automatic abstracting and indexing. II. Production of indicative abstracts by application of contextual inference and syntactic coherence criteria , Journal of the American Society for Information Science22(4) (1971) 260-274 .
26.
[26] R. Brandow , K. Mitze and L. Rau , Automatic condensation of electronic publications by sentence selection , Information Processing and Management31(5) (1995) 675-685 .
27.
[27] R. Barzilay and M. Elhadad , Using lexical chains for text summarization . In: I. Mani and M. Maybury (eds), Intelligent Scalable Text Summarization . Proceedings of a Workshop Sponsored by the Association for Computational Linguistics (Madrid, 1997).
28.
[28] H. Ahonen , Knowledge discovery in documents by extracting frequent word sequences , Library Trends48(1) (1999) 160-181 .
29.
[29] B.A. Mathis, Techniques for the evaluation and improvement of computer-produced abstracts. Technical Report OSU-CISRC-TR-72 (Ohio State University, Columbus, 1972).
30.
[30] K. Ono , K. Sumita and S. Miike , Abstract generation based on rhetorical structure extraction . In: COLING 94, Proceedings 15th International Conference on Computational Linguistics (Kyoto, 1994).
31.
[31] D. Marcu , From discourse structures to text summaries . In: I. Mani and M. Maybury (eds), Intelligent Scalable Text Summarization , Proceedings of a Workshop sponsored by the Association for Computational Linguistics (Madrid, 1997).
32.
[32] G. Chowdhury , Template mining for information extraction form digital documents , Library Trends48(1) (1999) 182-208 .
33.
[33] P. Jacobs and L.F. Rau , SCISOR: extracting information from on-line news , Communications of the ACM33(11) (1990) 88-97 .
34.
[34] P.M. Andersenet al. , Automatic extraction of facts from press releases to generate news stories . In: Third Conference on Applied Natural Language Processing (Trento, 1992).
35.
[35] Chong, A.G. , FIES: financial information extraction systems , Information Services and Use, 17(4) (1997) 215-223 .
36.
[36] P.A. Jones , C.D. Paice , A `select and generate' approach to automatic abstracting . In: T. McEnery and C.D.Paice (eds), Proceedings of the BCS 14th Information Retrieval Colloquium (Springer, Berlin1992).
37.
[37] G.J. Postma and G. Kateman , A systematic representation of analytical chemical actions , Journal of Chemical Information and Computer Sciences33(3) (1993) 350-368 .
38.
[38] N. Lawson , M.F. Kemp , G.G. Lynch and Chowdhury, Automatic extraction of citations from the text of English language patents: an example of template mining , Journal of Information Science22(6) (1996) 423-436 .
39.
[39] C.D. Paice and P.A. Jones , The identification of important concepts in highly structured technical papers . In: SIGIR-93: Proceedings of the Sixteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Association for Computing Machinery, New York, 1993).
40.
[40] R. Grishman , Information Extraction from Natural Language Text . PROTEUS Project Memorandum, no. 47. (Department of Computer Science, New York, 1991).
41.
[41] T.A. Van Dijk and W. Kintsch , Strategies of Discourse Comprehension ( Academic Press, New York , 1984).
42.
[42] K. Mackeown and D.R. Radev , Generating summaries of multiple news articles . In: E.A. Fox , P. Ingwersen and R. Fidel (eds), Proceedings 18th ACM-SIGIR Conference on Research and Development in Information Retrieval (Seattle, WA, 1975)
43.
[43] Columbia Natural Language Projects; www.cs.columbia.edu/nlp/projects.html (access date July 2002).
44.
[44] G. Dejong , An overview of the FRUMP systems. In: W.G. Rehnert and M. Ringle (eds), Strategies for Natural Language Processing ( Lawrence Erlbaum, London , 1982).
45.
[45] G. Fum , C.A. Guida and A. Tasso , A prepositional language for text representation. In: B.G. Bara and G. Guida (eds), Computational Models of Natural Language Processing ( North-Holland, Amsterdam , 1984).
46.
[46] L.F. Rau , Knowledge organization and access in a conceptual information system , Information Processing and Management (23)4 (1987) 269-283 .
47.
[47] B. Endres-Niggemeyer , Summarizing Information ( Springer, Berlin , 1998).
48.
[48] W.C. Mann and S.A. Thompson, Rhetorical Structure Theory: A Theory of Text Organization. Technical Report ISI/RS-87-190 (1990).
49.
[49] E.F. Skoroxod'ko , Adaptative Method of Automatic Abstracting and Indexing ( IFIP Congress, Yugoslavia , 1971).
50.
[50] U. Hahn and U. Reimer , Heuristic text parsing in `TOPIC': methodological issues in a knowledge-based text condensation system. In: Representation and Exchange of Knowledge as a basis of Information Processes ( North-Holland, Amsterdam , 1984).
51.
[51] G. Salton , J. Allan , C. Buckley and A. Singhal , Automatic analysis them generation and summarisation of machine-readable texts. In K. Sparck Jones and P. Willet (eds), Reading in Information Retrieval ( Morgan Kauffman, San Francisco, CA , 1997).
52.
[52] G. SaltonA. Singhal , M. Mitra and C. Buckley , Automatic text structuring and summarization , Information Processing and Management (33)2 (1997) 193-208
53.
[53] Mani and E. Bloerdorn , Multi-document summarization by graph search and matching . In: Proceedings of American Association for Artificial Intelligence (1997), pp. 622-628 .
54.
[54] F.W. Lancaster , Indexing and Abstracting in Theory and Practice ( Graduate School of Library and Information Science, University of Illinois, Champaign, IL , 1998), p. 293.
55.
[55] C.D. Paice , Automatic abstracting, In: Encyclopaedia of Library and Information Science ( Marcel Dekker, New York , 1994), Vol. 53(16), pp. 16-27.
56.
[56] T. C. Craven , Abstracts produced using computer assistance , Journal of the American Society for Information Science51(8) (2000) 745-756 .
