Name Index

Abelson, R.P., 298, 301
Abrial, J.R., 299
Adamowicz, M., 402
Addis, T.R.,297, 432
Aho, A.V., 351
Alouche, F., 195
Alter, S.L.,402
Andersen, A., 196
Anderson, B., 48
Arnold, R.S., 300, 403
Ashany, R., 402
Astrahan, M.M., 403
Attar, R„ 154, 252
Babbage, C., 304
Bach, E„ 298
Bachman, C.W., 403
Baker, N.R., 196
Barnett, J., 431
Barton, I.J., 114
Batcher, K.E., 349
Bates, M., 299
Baxendale, P., 112
Bayer, R., 350, 405

Becker, D.S., 154, 431
Bell, C.G., 351
Bely, N„ 195
Belzer, J., 192, 194-197
Benbasat, 1., 402, 406
Bennett, J.L., 402
Beranek, B., 300
Berger, M.C., 402
Berger, P., 402
Bergmark, D., 349
Bernstein, P.A., 403, 405
Berra, P.B., 349
Bhandarkar, D.P., 434
Bird, R.M., 351
Birnbaum, L., 298
Blasgen, M.W., 403
Bobrow, D.G., 298, 300, 301
Bohl, M„ 22, 349
Bole, L., 299, 301
Bookstein, A., 114, 115, 154,
195, 251,433
Borgida, A., 113
Bornstein, H., 192
Borodin, A., 253
Bourne, C.P., 48, 192, 196

Boyce, R.F., 404, 405
Boyer, R.S., 345, 351
Brachman, R.J., 299
Bracken, M., 434
Branscomb, L.M., 434
Brauen, T.L., 154, 253
Bray, O., 349, 352
Brookes, B.C., 194
Bryant, E.C., 192,
194-197
Buell, D.A., 433
Burch, J.G., 351
Burkhard, W.A., 350
Bush, V., 3, 21, 349, 435
Cadiou, J.M., 300, 403
Cameron, J.B., 252
Carlson, E.D., 22, 402
Carroll, J.M., 299
Casey, R.O., 404
Caswell, S.A., 21
Cavara, L., 194
Cawkell, A.E., 195
Cercone, N., 300
437

438

Chamberlin, D.D., 403-406
Chang, C.L., 300, 403
Chang, P.Y., 404
Chang, Y.K., 253
Chen, T.C., 349
Chomsky, N., 299
Cirillo, C., 253
Cleverdon, C.W., 102, 115,
193-196, 252
Climenson, W.D., 112, 192
Codd, E.F., 300, 403, 404, 406
Cohen, P., 113
Cole, J.R., 254
Cole, S., 254
Collins, A., 301
Comer, D., 350
Cooper, N.D., 196
Cooper, W.S., 110, 193, 195
Copeland, G.P., 349
Corasick, M.J., 351
Cors, R.C., 195
Crawford, R.W., 115
Creasey, S.E., 114
Croft, W.B., 114, 153, 251,
252
Cuadra, C.A., 48, 193
Cummings, M.M., 195
Damerau, F.J., 111-113, 298
Date, C.J., 402, 405
Dattola, R.T., 112, 252
Davidson, S., 154
Davis, G.B., 402
Davis, R., 402
Dell’Orco, P., 403
Delobel, C., 404
Dennis, S.F., 111
Dexter, M.E., 110
Dodd, G.G.,49
Dorf, R„ 22
Dorigan, J., 434
Doszkocs, T.E., 154, 155
Doyle, L.B., 112, 116
Duda, R.O., 433
Dunham, G.S., 113, 300
Durant, W., 348
Eason, K.D., 404
Eastlake, D., Ill, 434
Edelman, F., 402
Edmundson, H.P., 111, 112
Ellis, C.A., 434
Emery, J.C., 402
Eswaran, K.P., 403, 405
Fagin, R., 350, 404

NAME INDEX

Fairthorne, R.A., 193, 194
Fayen, E.G., 22, 23,48,49,
114, 155
Feng, E., 48
Fernandez, E.B., 404
Fife, D„ 48
Fillmore, C.J., 298
Findler, N.V.,298, 301
Fisher, J., 268
Fodor, J.A., 298
Ford, D.F., 196
Forgie, J.W.,431
Foskett, A.C., 21
Foster, C.C., 349
Fox, S., 405
Fraenkel, A.S., 154, 252
Francis, W.N., 111
Frank, R.L., 403, 406
Fraser, W., 299
Freeman, H.A., 349, 352
Freeman, W.H., 22, 255
Friedman, J., 113
Fry, J.P., 402, 406
Gabet, J.M., 21
Gardin, J.C., 195, 298
Garfield, E., 253-255, 434
Gerrity, T.P., 404
Ghosh, S.P., 404
Gibson, H.T., 404
Giddings, G.M., 402
Gilbert, H., 193
Gilchrist, A., 195
Gill, G„ 299
Giuliano, V.E., 112, 194, 252
Goffman, W„ 114, 193, 251
Goguen, J.A., 432
Goldberg, R.P., 404
Goldstein, G.D., 192, 194,
196, 197
Goldstein, R., 402, 406
Good, I.J., 196
Goodman, N., 405
Gotlieb, C.C., 22
Gotlieb, L.R., 22
Gottlieb, D„ 114
Graham, R.M., 405
Grauer, R.T., 252
Gray, J.N., 403-405
Gray, K., 298
Green, C., 431
Greenberger, M., 435
Griffith, B.C., 254
Griffiths, P.P., 403
Grishman, R., 113, 299, 300,
432
Grosz, B.J., 300
Gruenberger, F., 22

Gschwind, H.W., 351
Guazzo, M., 195
Hagerth, S.A., 114
Hagin, R., 402
Hall, P.A.,404
Hammer, M., 405
Handler, W„ 349
Hardwick, N.H., 112
Harper, D.J., 433
Harris, L.R., 113,300,403
Harris, R.T., 298
Hart, P.E., 433
Harter, S.P., 115
Hartigan, J.A., 255
Haskin, R., 351
Havron, M.D., 192
Hays, D.G., 113, 299
Heaps, H.S., 21, 113, 114, 254
Heine, M.H., 194
Heller, G.G., 195
Hendrix, G.G., 113, 299, 300,
403
Hillel, Y. Bar, 298
Hillman, D.J., 113, 154
Hirschman, L., 113, 300
Hollaar, L.A., 350
Hollerith, H„ 47, 304
Horowitz, E„ 22, 350, 405
Housel, B.C., 404
Howerton, P., 112, 252
Hsiao, D.K., 350
Huitfeldt, J., 21
Ide, E„ 153,253, 433
Jackson, D.M., 252
Jacobson, S.N., 112
Jardine, N., 251
Jones, G., 112
Jones, P.E., 112, 194, 252
Kannan, K., 350
Kaplan, R.M., 300
Karlgren, H„ 297, 298, 301
Kasarda, A.J., 113
Katter, R.V., 193
Katz, J.J., 298
Kay, M„ 112,297,298,300,
301,432
Keen, E.M., 110, 115, 193,252
Keith, N.R., 196
Keller, R.M., 350
Kelly, J., 253
Kemeny, J.G., 435

NAME INDEX

Kemp, D.A., 193
Keng, D.W., 197
Kent, A., 192, 194-197
Kern, E.M., 196
Kerr, D.S., 350
Kerr, L„ 253
Kessler, M.M,, 112, 254
King, D.W., 192, 194
King, M., 403
King, W.F., 403
Klaas, R.L., 402
Klatt, D„ 431
Klimbie, J.W., 299
Klingbiel, P.H., 299,432
Knaus, R., 434
Knottek, N., 349
Knuth, D.E., 350, 351
Kocheii, M., 114
Kofferman, K.I., 299
Roll, M.B., 154, 433
Korn, G.A.,351
Kraft, D.H., 115, 154, 195,
433
Kroenke, D„ 402, 405
Kucera, H., I ll
Kuhns, J.L., 114, 193, 251,
433
Kuno, S„ 112,298
Kwasny, S.C., 403
Lakoff, G.,432
Lam, K., 251
Lam, V.Y., 350
Lancaster, F.W., 21-23, 48,
49,110,114,115,155,.i 192-197,434
Landau, R.N., 402
Landers, C., 405
Larson, P.A., 350
Lawlor, J.C., 431
Lebowitz, M.L., 298
Lefkowitz, B., 196
Lefkowitz, D., 48
Lehnert, W., 300
Lehot, P.G.H., 114
Leiter, J., 155Lesk, M.E., 111, 112, 114,
153, 193, 194, 252, 253
Levy, F„ 195
Lewis, F., 253
Lewis, K., 299
Licklider, J.C.R., 431, 435
Lipovski, C.J., 349
Litofsky, B., 252
Lochovsky, F.H., 402
Lorie, R.A., 403, 405
Lorin, H., 405
Lovins, J.B., 111, 153
Low, D., 434

439

Lozano-Perez, T., 434
Luhn, H.P., 60, 66, 69, 111
Luk, W.S.,433
Lum, V.Y.,404
Lynch, M.F., 113, 114

MacCafferty, M., 298
McCarn, D.B.,49, 155
McCluskey, E.J., 351
McCreight, E., 350
McGee, W.C., 403
McGill, M.J., 21, 22, 154
McJones, P.R., 403
McLean, E.R., 402
McMurdo, G., 432
Mader, C.,402
Malthouse, N.S., 154
Mantey, P.E., 402
Marcus, R., 434
Marks, B.O.,434
Maron, M.E., 114, 193, 195,
197, 251,433
Marron, B., 48
Martin, W.A., 300
Martyn, J., 196, 403, 434
Masri, A. El, 350
Maugh, T.H., 11, 432
May, R.A., 111
Mayer, S.E., 192
Meadow, C.T., 22, 402
Meek, C.L., 349, 431
Meetharh, A.R., 194, 252
Mehl, J.W.,403
Messier, M., 252
Mills, J., 193, 1%
Minker, J., 22
Minsky, M., 298
Mitchell, P.C., 253
Montgomery, C.A., 112, 115,
297, 298, 432
Moore, J.S., 345, 351
Morris, J.H., 351
Mosteller, F., 114
Munson, J., 431
Mylopoulos, J., 113, 299, 403

Nance, R.E., 196
Nash-Webber, B., 300
Newell, A., 351,431
Newill, V.A., 193
Newsbaum, J.B., 351
Nguyen, H.B., 349
Nievergelt, J., 350
Noreault, T., 154
Norman, D.A., 300
Nutt, G.J., 434

O’Connor, J., 299,432
Oddy, R.N., 154, 251,253,‘ 433,434
Oettinger, A.G., 112, 298.bile, T.W.,403,406
Overbey, J., 434
Overhage, C.F.J., 432
Ozkarahan, E.A., 349
Pacak, M.G., 113, 300
Palmour, V.E., 195
Parhami, B., 349
Perreault, J., 195
Peterson, G.D., 196
Pippenger, N., 350
Plath, W.J., 113,299
Pollock, S.M., 195
Popplewell, C., 115
Porter, M.F., 433
Poulsen, M.J.F., 431
Pratt, A.D., 349
Pratt, A.W., 113,299, 300
Pratt, V.R., 351
Preece, S.E., 350
Price, C.E., 349, 350
Price, D.J. deSolla, 254
Putzolu, G.R., 403
Pyrce, S.R., 154
Rabinowitz, H.S., 114
Radecki, T., 432
Radhakrishnan, T., 113
Raghavan, V.V., 252
Ralston, A., 349, 431
Rankin, K., 48
Raphael, B., 22
Rapp, B.A., 154, 155
Razon, J., 253
Reddy, D.R.,431
Reeve, C., 405
Reimer, T., 403
Reintjes, J., 434
Report, D., 193
Rickman, J.T., 253
Riesing, T., 402
Rinker, C.C., 299, 432
Roberts, A.H., 299
Roberts, D.C., 350, 351
Robertson, S.E., 114, 193,
194,251,298,433,434
Robinson, A.L., 349
Rocchio, J.J., 153, 195, 253,
433
Rohmer, J., 350
Romerio, G.F., 194
Rosati, R.A., 402
Rosenthal, R.S., 349

440

Rothenberg, D.H., 196
Rothman, H., 115
Rothman, J., 49
Rothnie, J.B., 405
Roussopoulos, N., 113, 299,
300, 403
Rubinoff, M., 114
Ruhl, M.J., 115
Rumelhart, D.E.', 298
Rush, J.E., 112
Rustin, R., 301, 404
Sacerdoti, E.D., 300, 403
Sadowski, P.J., 349
Sagalowicz, D., 300, 403
Sager, N„ 113,298,300
Sahni, S., 22, 350, 405
Salton, G., 21, 22, 111-116,
153-155, 193-195,
251-254, 299, 349, 351,
432-435
Salvador, R., 112
Saracevic, T., 115, 193, 194,
197*
Sardana, K., 253
Schaaf, W.L., 348
Schank, R.C., 298, 301
Schecter, G., I ll
Schek, H.J., 113
Scherr, A.L., 405
Schipma, P.B., 431
Schmid, H.J., 299
Scholl, M„ 350
Schoolman, H.M., 155
Schuegraf, E.J., 113
Schumacher, A.W„ 192
Schuster, S.A., 349
Segmuller, G., 405
Segre, E., 4
Senko, M.E., 48, 402, 406
Shannon, C.E., 64, 111
Shapiro, S.C., 403
Shaw, T.N., 115
Shipman, D.W., 405
Shneiderman, B., 300
Shu, N.C., 404
Shumway, R.H., 194
Sibley, E.H., 402, 406
Sibson, R., 251
Siehler, C.J., 195
Silva, G., 298,432
Silver, G.A., 22
Silver, J.B., 22
Siu, M.K.,433
Slocum, J., 300, 403
Small, H.G., 155, 254, 434
Smith, J.M., 404
Smith, K.C., 349
Smith, L., 154, 349

NAME INDEX

Sneath, P.H.A., 255
Snell, M.J., 114
Snyder, M.B., 192
Sockut, G.H., 404
Soergel, D., 116
Sokal, R.R., 255
Sowa, J.W., 299
Spadavecchia, V.N., 403
Sparck-Jones, K., I ll, 112,
114, 153, 193,251,252,
254, 255, 267, 297, 298,
301,432,433
Starmer, C.F., 402
Steinacker, 1., 299
Stellhorn, W.H., 350
Stevens, M.E., 110, 115, 116
Stiles, H.E., 251
Stone, C.D., 114
Strater, F.R., 351
Strong, H.R., 350
Su, S.Y.W., 349
Suhler, W.C., 195
Summers, R.C., 404
Sussenguth, E.H., 350
Swanson, D.R., 101, 114, 115,
433
Swenson, J.R., 299
Swets, J.A., 177, 178, 194
Taeuber, D., 155
Tahani, V., 433
Tally, R.D., 154
Tars, A., 153
Taube, M., 22, 194
Taulbee, O.E., 192, 194-197
Taylor, R„ 403, 404, 406
Tell, B.V., 196
Thomas, R.H., 405
Thompson, H., 300
Todd, S.P., 195
Toffler, A., 4, 21
Traiger, I.L., 403-405
Trefftzs, J.L., 351
Treu, S., 192
Tsichritzis, D.C., 402
Tsotsos, J., 113
Tu, J.C., 351
Tusera, D., 350
Ullman, J.D., 402, 405
Urban, G.H., 115
Van Rijsbergen, C.J., 23, 49,
111, 114, 193, 197, 251,
433, 434
Vaswani, P.K.T., 252
Verhofstad, J.S.M., 405

Vernimb, C., 154, 253
Vickery, B.C., 110, 116, 196
Wade, B.W., 403
Walden, W.E., 253
Walder, J., 48
Waldstein, R.K., 114
Walker, D.E., 297, 298, 301
Wallace, E.L., 114
Waller, W.G., 154,433
Waltz, D.L., 113,300, 403
Wanger, J., 402
Watson, V., 403
Webb, K.W., 195
Wessel, A.E., 49
Wessel, C.J., 192
Westbrook, J.H., 254
Whitehead, J., 431
Wiederhold, G., 49, 402, 405
Wiederkehr, R.R.V., 194-196
Wilde, D„ 22
Wiley, J., 403
Williams, G., 195
Williams, J.H., 154, 253
Williams, M.E., 21, 112, 298
Williariis, P.W., 251, 349, 433,
434
Williamson, D., 193
Williamson* R.E., 153, 193
Winningstad, C.N., 349
Winograd, T., 298, 300
Winslow, K.S., 431
Winston, P.H., 22, 298
Winter, R.A., 434
Wise, P., 112
Withington, F.G., 2l, 349
Woelfle, R.M., 431
Wong, A., 116, 153
Wong, E., 405
Wong, H.K.T., 113,403
Wood, C., 404
Woods, W.A., 113,299, 300,
431,432
Worthy, R.M., 351
W u,H „ 251,252, 433
Wyllys, R.E., 111
Yang, C.S., 111, 153
Yao, S.B.,404
Yu, C.T., 111, 114, 153,251,
252, 433
Zadeh, L.A., 432
Zamora, A., 112
Zani, W.M., 402
Zipf, G.K., 60, 111
Zloof, M.M.,403
Zunde, P., 110Subject Index

Abridged Index Medicus (AIM), 42
Abstract, 29, 259, 355
Access control, 390-394
Adjacency, term, 28-29, 37-40, 258
Aggregate operations, 387
AIM-TWX retrieval system, 42
Algebra (see Relational algebra)
Ambiguity (see Linguistic ambiguity)
Anaphoric expression, 292
AND operations (see Boolean retrieval)Answer-indicative passage, 284
Answer-reporting passage, 284
Array processor, 317-318, 320-322
Associative processor, 317
ATN (augmented transition network) grammars,
276-284
Attribute value, 357, 363-364(See also en tries b eg in n ing w ith th e w ord:

Term)
Augmented transition network (ATN)
grammars, 276-284
Authorization, 391-392
Automatic abstracting, 259
Automatic classification, 80-81, 220-222(See also Pseudoclassification)
Automatic indexing, 52-110, 127-136
Automatic query adjustment (see Queryreformulation)

Automatic sentence extraction (see Sentence
extraction)
Automatic thesaurus construction (seeThesaurus construction)
Automatic translation, 261-262
Averaging, 167, 169, 218
B-tree, 334-338
Back-end processor, 146, 315-326
Backtracking method, 278-280, 284, 341
Back-up copy, 360, 398
Bahadur-Lazarsfeld expansion, 423
Base component, 275
Bayes rule, 96
BCNF (Boyce-Codd normal form), 394
Benefit-cost analysis, 190
Bibliographic attribute vector (see Term vector)
Bibliographic citation, 84, 246-250, 426-427
Bibliographic coupling, 248-250
Bibliographic reference, 246
Bibliographic retrieval (see Information retrieval
system)Bibliographic Retrieval Services (BRS) system,
41-42
Binary indexing, 201
Binary search, 15-16, 330-331
Binary term weighting (see Term weighting)
441

442

Binomial distribution, 96
Boolean expression, 25-26
Boolean retrieval, 25-28, 37-38, 148-150,
211-215
Bottom-up search, 137, 219
Boyce-Codd normal form (BCNF), 394
Boyer and Moore string search method, 345-348
Broader term, 57, 76
BROWSER system, 149
Browsing, 120, 200, 209
BRS (Bibliographic Retrieval Services) system,
41-42
Bucket, 333-334
Buffer, 310-311, 315, 326
Cache memory, 309
Call number, 3
Candidate key, 366, 392
Canonical representation, 92
Cartesian product, 368-370, 386-390
Case grammar, 263
CASSM processor, 322-324, 339
Catalog, 2-4, 53, 188
Cathode-ray tube, 312, 418 •Cause-effect (see Term associations)
Cell processor, 309-310, 322-326
Centroid (see Cluster centroid)
Chaining of records, 371-372, 378
Channel, 311
Character comparison, 340-345
Character reading, 411-413
Checkpoint, 398
Child record (see Hierarchical data base model)
Chip, 312-313, 339, 409
Citation (see Bibliographic citation)
Citation index, 104, 247
Citation network, 248, 249
Citation search, 248-250
Classification (see Automatic classification;
Document classification; Term clustering)
Classification matrix, 231
Clique, 80, 137, 220
Cluster centroid, 66, 80-81, 125-126, 213,
217-218
Cluster feedback (see Relevance feedback)
Cluster generation, 137-140
Cluster hypothesis, 215
Cluster search, 137-140, 222-227
Cluster search evaluation, 222-227
Cluster splitting, 138-139
Clustered document file, 124-128, 137-140,
215-222
Clustering (see Document classification; Termclustering)
COBOL programming language, 377
Cocitation link, 248-250, 426-427
CODASYL, 377
Cohesion factor, 85
Collection completeness, 2, 162

SUBJECT INDEX

Collection coverage, 162, 177, 187
Collection currency, 2Collection growth, 245-246
Collection retirement, 245-246
Collision in hash table, 333
COMBINE operation for document sets, 31-32
Commit point, 398
Communication channel; 7Communication network, 7Communication theory, 64-65
Comparand register, 317-320
Completeness, collection, 2, 162
Composite document representation, 425-426
Compression, text, 93-94
Computer-aided indexing, 91-92
Computer architecture, 312-314
Computer network, 315
Concentration, term, 65-66, 85
Conceptual dependency, 264
Conceptual network, 288-291
Conceptual schema (see Schema)
Concordance, 78, 259
Concurrency in data base, 394-398
Connected component, 220
Connective (see Boolean retrieval)Constituent structure, 270-272
Content analysis (see Language processing)Context-free grammar, 91, 268-273
Context-sensitive grammar, 273-276
Contiguous terms, 344
Contingency table, 177, 185, 194
Contour map, 249
Controlled index term, 54, 101, 119
Controlled vocabulary, 11
Conventional retrieval, 30-48, 118-120
Co-occurrence, term, 258-259, 423
Copy of transaction, 398-400
Core, magnetic, 306, 308-309
Core document, 425
Correctness of data (see Data integrity)
Correlation coefficient (see Similarity measure)
Cosine coefficient, 121, 124, 203
Cost analysis, 187-192
Cdst-benefit analysis, 186, 189
Cost components (see Cost analysis)
Cost-effectiveness evaluation, 186
Cost-time-volume model, 188
Cost and value parameters, 185-186
Coverage, collection, 162, 177, 187
Cranfield experiment, 101-103
Crash recovery, 398-399, 401
Criterion tree, 285-287
Cue word, 89
Currency, collection, 2Currency pointer, 378
Data base, 360
Data base computer, 326-328

SUBJECT INDEX

Data base management system, 8, 354-401
Data base model:
hierarchical, 370-377
network, 377-380
relational, 365-370
Data base network, 400
Data base set, 378
Data Base Task Group (DBTG), 377-380
Data cell, 309-310
Data description language, 361
Data dictionary, 362
Data encryption, 391
Data independence:
logical, 360-361
physical, 360-361
Data integrity, 390-394
Data loop, 326-327
Data management (see Data base management
system)Data manipulation language (see QBE system;
SEQUEL language)
Data quality, 359, 390-394
Data retrieval (see Data base management
system)Data security, 360, 390-394
DBTG (Data Base Task Group), 377-380
Deadlock prevention, 395-396
Decision support system, 7, 9, 358-359
Decomposition of relations, 394
Deductive system, 259, 356, 420
Deep indexing, 55
Deep structure of language, 275
Default exit, 343
Delay cost (see Cost analysis)
Density (see Document space density)
Dependency (see Functional dependency; Term
dependency model)
Depth-first search, 223
Descriptive cataloging, 53
Deterioration, 225-226, 233
DIALOG system, 30-34, 38, 46-48
Dice coefficient, 203
Dictionary, 56-57, 101-103, 259-263, 285-286
Dictionary format, 57
in STAIRS, 36
Digital search tree, 337-338
Direct access search, 332-333
Direct file, 17
Directory (see Dictionary; Inverted file)
Disambiguation, 295, 356
Discontinuous constituent, 271-272
Discriminant function, 95-99
Discrimination value (see Term discrimination
value)
Disk, 307-315, 324-328, 413-415
Disk controller, 340
Distance (see Document space; Similarity
measure)Distributed data base, 399-401

443

Document classification, 137-140, 215-222(See also Clustered document file)
Document cluster (see Clustered document file)
Document frequency, 67
Document indexing (see entries beginning w ith
the w ord: Indexing)
Document input, 410-413
Document-level average, systems-oriented, 169
Document ranking (see Ranked output)
Document retirement, 245-246
Document scope, 425
Document space, 122, 128, 145, 245
Document space density, 66-67, 205
Document vector modification (see Dynamic
document space)“ Don’t care” character, 32, 343, 346
Drum, 306, 309-310, 315
Dummy attribute, 383-384
Dynamic document space, 145-146, 244-246
Dynamic hashing, 333
Dynamic tree search, 334-338
E measure, 177-180
Efficiency, retrieval, 158, 186-192
Encryption, 390
Entity, 363
Error in data (see Data integrity)
Estimated entry search, 332
Evaluation (see Retrieval evaluation)
Evaluation measure, 162, 164-172
Exhaustivity, indexing, 55, 160
Expected search length, 182-183
Extendible hashing, 333-334
External schema (see Schema)
Factor analysis, 425
Fallout measure, 174-178, 181, 191
False drop, 94
Fast arithmetic, 320-322
Feedback (see Relevance feedback)Fiche (see Microfiche)
Field, 8, 33-34, 41-43
File organization, 3-7, 12-20, 35-36, 43-44,
124-127, 386-388
File reorganization, 387-388
Film, 416-417
Finite state automaton, 276-284, 340-345
First normal form, 393
Fixed cost, 188
Floating point arithmetic, 320-321
Floppy disk, 307-308, 312, 410
Fragment (see Word fragment)
Frame, 265-266
Free text, 36
Frequency (see Document frequency; Termfrequency)
Full text retrieval, 46-48, 428

444

SUBJECT INDEX

Functional dependency, 365, 392-394
Fuzzy set, 150-151,421-425
Generality factor, 174-175
Generative grammar, 268
Governing-descendant relation (see Term
associations)
Grammatical models, 257
Graph-theoretical clustering, 220-222
Graphics, 408-409, 413, 418
Grouping (see Document classification; Termclustering)

Hand calculator, 312-313
Hardware approach, 303-329, 339-340
Hash table, 332-333
Hashing method, 332-334, 377
Heuristic clustering, 216, 221-222, 232-234
HIDAM (hierarchical direct access method), 376
Hierarchical access methods, 376-377
Hierarchical data base model, 370-377
Hierarchical dictionaries, 56
Hierarchical direct access method (HIDAM),
376
Hierarchical grouping, 137
Hierarchical relations, 56-57, 130-131, 364-367
Hierarchical sequential access method(HISAM), 376-377
High-level query language, 380-381
HISAM (hierarchical sequential access method),376-377
Hologram, 416-417
Host computer, 315-316, 320-328

IDS/1I system, 377
IMS (Information Management System),
376-377
Independence (see Data independence)
Index {see Inverted file)Index term {see en tries beginning w ith the word:
Term)
Indexed file, 16-20{See also Inverted file)Indexed search, 332
Indexed sequential storage system, 376
Indexing, automatic, 52-110, 127-136
Indexing consistency, 59, 160
Indexing exhaustivity, 55, 160
Indexing language, 10-12, 160
Indexing specificity, 55, 75, 160, 187
Indexing time vs. search effectiveness, 187
Indicative abstract, 259
Information Bank, 45-46
Information request, 11{See also en tries b eginning w ith the word:

Query)

Information retrieval machine, 339-340{See also Hardware approach)
Information retrieval system, 1, 7-8, 30-48,
355-356
Information system types, 7-10
{See also Information retrieval system)
Information technology, 5-6, 303-329, 408-418
Information theory, 63-66
INSPEC retrieval service, 362
Integrity, data, 390-394
Intelligent information system, 426-427
Interactive retrieval, 237-238{See also Dynamic document space; Relevance
feedback)
Interference pattern, 416-417
Interindexer consistency {see Indexing
consistency)
Internal schema {see Schema)
Interpolation, 167
Inverse document frequency, 63{See also Term weighting)Inverted directory {see Inverted file)
Inverted file, 24-27, 120, 147, 311, 387-390
HISAM, 375-377
indexed files, 16-20
MEDLARS system, 42-43
references and exercises, 48-51
Item-by-item search, 15
Iterative partitioning, 137
Iterative search {see Relevance feedback)Jaccard coefficient, 203
Join operation in relational algebra, 369-370,
389-390, 394
Journal checkpoint, 398
Journal of transactions, 398
Key (see Candidate key; Search key)
Keyword decoding unit, 327
Keyword-in-context (KWIC) index, 78
Knowledge base, 262, 264
Knowledge representation, 287-291
Laboratory Animal Data Bank, 386
Language processing, 257-297, 420-421
Language understanding system, 257, 261-266
Laser, 414-416
Least effort, 60
Least recently used (LRU) page replacement,
224-225
Lexical process (see Dictionary; Thesaurus)
LEXIS system, 46
Library, 2-3, 6, 12(jLinear list, 12-13
Linear scan, 330
Linguistic ambiguity, 292-297, 356, 420-422
Linguistic method, 90-92

SUBJECT INDEX

Linguistic primitive, 264
Linking of terms, 56(See also Hierarchical data base model;
Network data base model)
List merge network, 329
List processing, 376
Livelock, 395-396
Local clustering, 152
Local thesaurus, 152
Location, term, 29, 37
Location transparency, 400
Lock manager, 395-396
Locking mechanism, 395-398
Logical file organization, 3
Logical pointer, 374-375
Logical relationship, 372-373
Loss parameter, 95-96
Lossless join, 394
Low-level query language, 380-381
LRU (least recently used) page replacement,
224-225LSNLIS system, 292-294
Machine translation (see Automatic translation)
Magnetic core, 306, 308-309
Magnetic disk, 307-308
Magnetic tape, 306-307
Man-machine dialogue, 151-152
Management information system, 8Manual indexing, 53-59, 102
Many-to-many relationship, 377-380
Many-to-one relationship, 371-373, 377-380
Mask register, 317-319
MEDLARS system, 42-45, 103-105
Member record type, 378
Membership function, 421
Memex, 312
Memory (see Storage devices)
Menu display, 381-382, 386
Metal oxide semiconductor (MOS), 308
Metric retrieval, 33, 133
Microcomputer, 310-311, 313(See also Microprocessor)
Microfiche, 417-418
Micrographic storage, 417-419
Microprocessor, 310, 312-314, 430
Minicomputer, 78, 315
Mixed retrieval systems, 426-428
Model, data base (see Data base model)
Morphological process, 259-260(See also Term truncation)
MOS (metal oxide semiconductor), 308
Multiple key search, 338-339
Multiple processors (see Parallel processors)
Multiple term detection, 344
Multiplexor channel, 311
Multiprocessor system, 317
Narrower term, 57, 76

445

Natural join, 370
Natural language (see Language processing)
Navigation in data base, 377
Negative feedback, 242-243
Network data base model, 377-380
Network transformation rules, 290
N e w Y o rk T im es Information Bank, 45-46
Node splitting, 336-337
Noise (see Signal-noise ratio)
Nonterminal node, 270-275
Normal form, 393-394
Normalized evaluation measure, 168-170,
180-181Normalized precision, 180-181
Normalized recall, 180-181
NOT operation (see Boolean retrieval)Noun phrases (see Language processing)
Novelty ratio, 176
Office automation system, 428-430
On-line retrieval, 42, 45-46(See also Interactive retrieval)
One-to-one relationship, 371-373
Operating characteristics, 178-179
Operating cost, 188
Optical character recognition, 411-413
Optical fiber, 7
Optical storage, 413-418
OR operation (see Boolean retrieval)
ORBIT system, 45
Order of operations, 26-28
Overflow condition, 333-334
Overlap measure, 203-204
Overlapping cluster, 220-221
Owner record type, 378
Page transfer, 224-226
Paperless information system, 408-409, 428-430
Parallel processors, 316-317, 320-322
Parent-child relation, (see Term association)
Parse tree, 90-92
Partial dependency, 394
Partitioned file, 400
Passage retrieval, 284-285, 355-356
Password, 390-391
Performance measurement, 188, 313(See also Retrieval evaluation)
Permuted title index, 57-58
Personal computing system, 428-430
Pertinence, 163, 193
Phonological component, 259
Photocopying system, 430
Phrase, term, 84-87, 128, 132-134
Phrase evaluation, 109
Phrase marker, syntactic, 293
Phrase structure grammar, 268-273
Phrase transformation, 87
Phrase weight, 133

446

Physical organization, 3
Physical pointer, 373-375
Pipelining, 320, 327
Pointer structure, 365, 371, 388
Poisson distribution, 96, 99
Pop exit, 276-278, 280
Positive feedback operation, 144, 240-241
Postcoordination of terms, 55-56
Postings file, 42-43
Pragmatic language processing, 260
Precision measure, 55, 104-109, 160, 162,
164-172
Precoordination of terms, 55-56
Predicate calculus, 289
Prefetch method, 224, 226
Preorder tree traversal, 376
Prepositional phrases (see Language processing)
Prestel service, 403n., 434n.
Primary key, 366
Primitive concepts, linguistic, 264
Principle of least effort (see Zipf law)
Probabilistic indexing, 205-206, 422-424
Probabilistic retrieval, 94-99
Probability of relevance, 95-98
Project operation in relational algebra, 368
Pronoun reference resolution, 294
Protection of data, 390, 401
Protocol of operations, 396-397
Pseudoclassification, 227-236(See also Automatic classification)
Punched card, 304-306
Push-down store, 277-279
QBE system (see Query-by-example system)
Query analysis, 160-161 ■Query-by-example (QBE) system, 382-384,
391-394
Query centroid, 223-224
Query document similarity (see Similarity
measure)Query formulation, 388-390(See also Relevance feedback)
Query language type, 380-386
Query negotiation, 11
Query optimization, 329, 388-390
Query reformulation, 123-124, 142-145,
236-243(See also Relevance feedback)
Query splitting, 242
Query type, 173
Query vector (see Term vector)
Question-answering system, 9, 92, 259, 291-297,
355-356

Random access device, 308-310
Rank-frequency law, 60-61
Rank mode in STAIRS, 40-41

SUBJECT INDEX

Rank value, 218
Ranked output, 47-48, 146-149
RAP processor, 324-326, 339
Recall-fallout graph, 175-178, 181, 197
Recall-level average, 168
Recall measure, 55, 104-109, 160, 162, 164-172
Recall-precision graph, 105-106, 165-172, 176,
179, 182, 187, 197, 243,256, 322
Recognition dictionary, 285
Record, 8, 15-18, 95-97, 304, 307, 380-398
Record identifier, 331
Record type, 371
Recovery method, 398-399
Recursive program, 331
Reference (see Bibliographic citation)
Reference string (see Word fragment)
Reformulation (see Query reformulation)
Relation, 366-372, 385-390
Relation scheme, 366
Relational algebra, 366-370, 385
Relational associative processor (see RAP
processor)
Relational data base model, 365-370
Relational operators, 39
Relationship between entities, 363-364(See also Term associations)
Relative frequency (see Term frequency)
Relevance assessments, 141, 163-164, 173, 232
Relevance feedback, 123-124, 140-145,
236-243, 424
Relevance matrix, 229
Relevance weight (see Term relevance factor)
Reorganization, file, 387-388
Replica transparency, 400
Replication, 400
Request (see Information request; entries
beginning w ith th e w ord: Query)
REQUEST system, 295
Resolving power of terms, 62
Resource locking (see Locking mechanism)
Response time, 162
Restart method, 398-399
Restricted join, 369-370
Retrieval effectiveness, 158-186
Retrieval efficiency, 158, 186-192
Retrieval evaluation, 157-192, 207-211,222-227
Retrieval matrix, 229
ROBOT system, 295
Role of term, 56
Rollback operation, 396
Root of tree in hierarchical systems, 375-376
Sampling method, 159, 166
Scatter storage method, 332-333
Scheduler, 396
Schema:conceptual, 360-361
external, 361
internal, 361

SUBJECT INDEX

Science Citation Index (SCI), 104
Scope notes, 54
Script, 265, 291
Search intermediaries, 119
Search key, 13-18, 331-338
Search operation, 161, 330-339
Second normal form, 393
Security, data, 360, 390-394“ See” reference, 56“ See also” reference, 56-57
Seed point, 137
Select-from-where clause, 384-385
Select mode in STAIRS, 39
Select operation in DIALOG, 31-33
Selection operation in relational algebra, 367,
389-390
Selector channel, 311
Semantic analysis, 131-133, 259-269, 290-299
Semantic interpretation rules (see Language
processing)Semantic net, 265, 288-291
Semiconductor technology, 308
Sentence extraction, 87
Sentence generation, 268-275
SEQUEL language, 384-386
Sequential file, 13-16
Sequential search, 329-330, 334, 339
Serializable schedule, 396-398
Set difference, 25-26
Set intersection, 25-26
Set union, 25-26
Sign test, 171
Signal-noise ratio, 63-66, 107-108
Similarity measure, 66, 78-79, 121, 201-204,
236, 322, 426
Simulation of system, 188-189
Single-link clustering, 134-137, 220Single-pass clustering, 137-138
Single-valued measure, 177-186
SIRE system, 148-151
Sliding ratio measure, 183-184“ Smart” peripheral device, 315, 324
SMART system, 118-146, 285-287
SMART system experiments, 101-110
MEDLARS compared with, 103-106
Software approach, 303, 329-347
Sorting, 389-390
Specificity (see Indexing specificity)
Speech recognition, 409
Speech understanding, 409, 413
Splitting, node, 336-337
SQL (SEQUEL) language, 384-386
Stable process, 216, 221
Stack, 277-279
STAIRS system, 34-41
Staran processor, 319-320
Statistical significance, 105-109
Stem (see Word stem)
Stop list, 71-72, 131

447

Storage devices, 305-312
Storage technology, 6
String analysis, 295-296
String searching, 43-44, 340-348
Structure of language, 275-276
Structure loop, 326-327
Structure memory, 327-328
Subject catalog, 3
Subject indexing (see entries beginning w ith thew ord: Indexing)
Subschema, 390-391
Suffix cutoff, 71-73
Suffix list, 73
Supercentroid (see Cluster centroid)
Superimposed coding, 338-339
Surface structure of language, 275-276
Swets’ E measure, 177-180
Synonym, 38, 101-103
Synonym dictionary (see Thesaurus)
Syntactic analysis, 90-92, 131, 260, 267-287, 293
Syntactic coherence, 88
Syracuse Information Retrieval Experiment (seeSIRE system)t test, 106-109, 171
Tabular query language, 382-384
Tape, 306-312
Tape cassette, 311
Technology (see Information technology)
Teletext, 429
Teletypewriter Exchange Network (TWX), 42
Television, 414-415
Term adjacency, 28-29, 37-40, 258
Term assignment, 121(See also entries beginning w ith the w ord:Indexing)
Term association measure, 234-235
Term associations, 75-76, 80-82, 233-236,
363-364
Term centroid, 80-81
Term classification (see Pseudoclassification;
Term clustering)
Term clustering, 135-136, 215, 227-236
Term concentration, 65-66, 85
Term co-occurrence, 258-259, 423
Term deletion, 74-75, 106-107, 132-133
Term dependency model, 422-424
Term detector, 339-340
Term discrimination value, 66-71, 103-110,
205-206
Term extraction, 59-75
Term frequency, 30, 40, 60-62, 97-98, 105-109,
132, 208-210
Term independence, 97
Term location, 29, 37
Term phrase, 84-87, 128, 132-134
Term precision (see Term relevance factor)
Term relations (see Term associations)

448

SUBJECT INDEX

T erm

r e le v a n c e fa c t o r , 9 8 , 2 0 6 -2 1 0 , 4 2 3

T w o -p h a s e lo c k in g , 3 9 6 -3 9 7

T erm

s im ila r ity , 7 9 - 8 0

T y p e s e ttin g , 428(S eea ls o T e r m

a s s o c ia tio n s )T erm

s p e c ific ity , 6 4 , 7 5

T erm

tr u n c a tio n , 3 1 - 3 2 , 4 3 -4 4 , 7 1 - 7 3 ,T erm

v a lu e , 4 0(S ee

a ls o T e r m

U n c o n tr o lle d v o c a b u la r y , 11
U n d e r s ta n d in g (se e L a n g u a g e u n d e r s ta n d in gsy ste m )w e ig h t in g )U n it c o s t , 18 8

T erm

v e c to r r e p r e s e n ta tio n , 1 2 1 - 1 2 2

T erm

w e ig h t e v a lu a tio n , 2 0 7 -2 1 1

T erm

13 1-13 4

U n r e s tric te d jo in , 3 70
U se r e ffo r t, 16 2

w e ig h t in g , 4 7 , 5 9 - 7 5 , 1 3 2 , 1 4 1 , 1 4 6 - 1 4 8 ,
2 0 4 -2 0 6

U s e r fe e d b a c k (s e e R e le v a n c e fe e d b a c k )U s e r fr ie n d lin e s s , 3 5 9 , 3 8 0 -3 8 1

in B o o l e a n s y s t e m , 2 1 1 - 2 1 5U se r s c h e m a (see S c h e m a )T e r m i n o lo g y lis t ( s e e D ic t io n a r y )U se r-sy ste m

T e s t a n d c o n tr o l e v a lu a tio n , 2 4 3 -2 4 4in t e r a c t io n , 1 5 1 - 1 5 2

U t ilit y m e a s u r e , 1 8 4 - 1 8 6 , 2 0 6 -2 1 0

T e s tin g (s e e R e tr ie v a l e v a lu a t io n )T e x t a c c e ss, 3 2 9 -3 4 8
T e x t c o m p r e s s io n , 9 3 -9 4

V a lu e p a r a m e te r , 18 5

T e x t m a t c h in g (s e e S t r in g s e a r c h in g )V e c to r (see T e rm

T e x t s c a n n in g m a c h in e , 3 3 9 -3 4 0

V e c t o r s im ila r ity (s e e S im ila r ity m e a s u r e )T e x t s e a r c h (s e e S t r in g s e a r c h in g )V e c to r sp a c e (see D o c u m e n t sp a ce)

T e x tu a l in fe r e n c e , 88

V id e o d is p la y , 4 1 1

T h e sa u ru s, 7 5 -8 4 , 1 0 1 -1 1 2 ,

1 2 8 -13 6 , 1 5 2 -1 5 3 ,19 9 -2 0 0 , 2 3 0 - 2 3 3 ,2 5 9 - 2 6 0v e c to r r e p re s e n ta tio n )V id e o d is c d e v ic e , 4 1 4 - 4 1 7
V L S I te c h n o lo g y , 4 2 9( S e e a ls o D i c t i o n a r y )V o c a b u la r y (seeT h e s a u r u s c la s s , 13 2e n tr ie s b e g in n in g w ith th e w o rd :T erm )

T h e s a u r u s c o n s t r u c tio n , 7 7 - 8 1 ,

13 4 -13 6

V o ic e in p u t, 4 1 3T h e s a u r u s e v a lu a tio n , 10 9
T h e s a u ru s tr a n s fo r m a tio n , 8 7

W e ig h te d in d e x in g , 7 4 , 2 0 1 -2 0 6

T h e sa u ru s u se, 8 1-8 4
T h ir d(S ee

n o rm a l fo rm , 393

W ord

T r a n s a c tio n m a n a g e m e n t, 3 6 0 , 3 9 5 -4 0 2
T ra n s fo r m a tio n a l c o m p o n e n t, 2 7 4 -2 7 5T ra n s fo r m a tio n a l g ra m m a r, 9 2 , 2 7 3 -2 7 6n e tw o rk g ra m m a rs)
T r a n s la tio n , a u to m a tic , 2 6 1 -2 6 2
T r e e d e p e n d e n c e m o d e l, 4 2 3

tr a n s itio n(see

e n tr ie s b e g in n in g w ith th e w o rd :T erm )
W ord

d is ta n c e (s e e M e tr ic r e tr ie v a l)

W ord

fr a g m e n t, 9 3 -9 4

W ord

lo c a tio n , 89

W ord

p r o c e s s in g s y s te m , 4 1 0

W ord

ste m , 1 3 3 -1 3 4(S eea lso T e r m

T ree sea rch , 2 1 8 -2 19 , 2 2 4 -2 2 6
T r ie , 3 3 7 -3 3 8
T r u n c a tio n (s e e T e r m

Y e s/ n o q u ery, 381
tr u n c a tio n )T u p le , 3 6 6 -3 7 0
T w o -p h a s e c o m m it p o lic y , 3 9 8 -3 9 9

w e ig h t in g )W ilc o x o n s ig n e d r a n k te s t , 1 0 6 - 1 0 9 , 1 7 1

T o p -d o w n sea rch , 2 19

T r a n s itio n n e tw o r k (se e A u g m e n te da lso T e r m

W e ll-d e fin e d c la s s ific a tio n , 2 1 6T im e ( m a g a z i n e ) c o l l e c t i o n , 1 0 5 - 1 0 9

Z ip f la w , 6 0 -6 1'

tr u n c a tio n )