- 1 BERGE, C. The Theory of Graphs and Its Applications. Wiley, New York, 1962.Google Scholar
- 2 BIRKtIOFF, G. Lattice Theory (rev. ed.). Amer. Math. Soc. Colloq. Publications, Amer. Math. Soc., Providence, R. I., 1948.Google Scholar
- 3 BONNER, R.E. On some clustering techniques. IBM J. Res. Devel. 8, 1 (Jan. 1964), 22-32.Google Scholar
- 4 CLEVERDON, C.W. Report on the testing and analysis of an investigation into the comparative efficiency of indexing systems. ASLIB-Cranfield Research Rep., Oct. 1962. Cranfield, Bedford, England.Google Scholar
- 5 ENGINEERS JOINT COUNCIL. Thesaurus of Engineering Terms (lst ed.). New York, May 1964.Google Scholar
- 6 GIULIANO, V. E., AND JONES, P.E. Linear associative information retrieval. In Howerton, P. W., and Weeks, D. C. (Eds.), Vistas in Information Handling, Vol. I, Spartan Books, Washington, D. C., 1963, Ch. 2, pp. 30-46.Google Scholar
- 7 LEWIS, P.A. W., BAXENDALE, P. B., AND BENNETT, J.L. Statistical discrimination of the synonymy/antonymy relationship between words. J. ACM i$, 1 (Jan. 1967), 20-44. Google Scholar
- 8 LInRAaY OF CONGRESS. Subject Headings (6th ed.). Washington, D. C., 1957.Google Scholar
- 9 MARON, M. E., AND KUHNS, J.L. On relevance, probabilistic indexing and information retrieval. J. ACM 7, 3 (July 1960), 216-244. Google Scholar
- 10 MEETHAM, A.R. Graph separability and word grouping. Proe. 21st National Conference ACM, July 1966 (ACM Pub. P-66). Thompson Book Co., Washington, D. C., pp. 513-514. Google Scholar
- 11 NEEDHAM, R.M. Applications of the theory of clumps. Mech. Transl. Comput. Linguist. 8 (June and Oct. 1965), 113-127.Google Scholar
- 12 RIAL, J. F. A pseudo-metric for document retrieval systems. Rep. W4595, The Mitre Corp., Bedford, Mass.Google Scholar
- 13 RoccHio, J .J . Document retrieval systems--optimization and evaluation. Harvard U. doctoral th., Rep. No. ISR-10 to the National Science Foundation, Harvard Computation Lab., March 1966.Google Scholar
- 14 SALTON, G. Associative document retrieval techniques using bibliographic information. J. ACM 10, 4 (Oct. 1963), 440-457. Google Scholar
- 15 SPXRCK-JONES, K. Experiments in semantic classification. Mech. Transl. Comput. Linquist. 8 (June and Oct. 1965), 92-112.Google Scholar
- 16 STEVENS, M. E. (Ed.). Proc. Symposium in St.~tistical 'Assocb~tion Methods for Mechanized Documentation. US Government Printing Office, NBS Misc. Pub. 269, Dec. 1965.Google Scholar
- 17 STILES, H .E . The association factor in information retrieval. J. ACM 8, 2 (April 1961), 271-279. Google Scholar
- 18 US DEPARTMENT OF HEALTH, EDUCATION AND WELFARE. MEDLARS Medical Subject Headings (3rd ed.). Washington, D. C., Jan. 1964.Google Scholar
Index Terms
- Semantic Clustering of Index Terms
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