-
He, W.; Tian, X.: ¬A longitudinal study of user queries and browsing requests in a case-based reasoning retrieval system (2017)
0.01
0.009593869 = product of:
0.044771384 = sum of:
0.017435152 = weight(_text_:web in 3600) [ClassicSimilarity], result of:
0.017435152 = score(doc=3600,freq=2.0), product of:
0.09670874 = queryWeight, product of:
3.2635105 = idf(docFreq=4597, maxDocs=44218)
0.029633347 = queryNorm
0.18028519 = fieldWeight in 3600, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2635105 = idf(docFreq=4597, maxDocs=44218)
0.0390625 = fieldNorm(doc=3600)
0.012357258 = weight(_text_:information in 3600) [ClassicSimilarity], result of:
0.012357258 = score(doc=3600,freq=12.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.23754507 = fieldWeight in 3600, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=3600)
0.014978974 = weight(_text_:retrieval in 3600) [ClassicSimilarity], result of:
0.014978974 = score(doc=3600,freq=2.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.16710453 = fieldWeight in 3600, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=3600)
0.21428572 = coord(3/14)
- Abstract
- This article reports on a longitudinal analysis of query logs of a web-based case library system during an 8-year period (from 2005 to 2012). The analysis studies 3 different information-seeking approaches: keyword searching, browsing, and case-based reasoning (CBR) searching provided by the system by examining the query logs that stretch over 8 years. The longitudinal dimension of this study offers unique possibilities to see how users used the 3 different approaches over time. Various user information-seeking patterns and trends are identified through the query usage pattern analysis and session analysis. The study identified different user groups and found that a majority of the users tend to stick to their favorite information-seeking approach to meet their immediate information needs and do not seem to care whether alternative search options will offer greater benefits. The study also found that return users used CBR searching much more frequently than 1-time users and tend to use more query terms to look for information than 1-time users.
- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1124-1136
-
Chen, Z.: ¬A conceptual model for storage and retrieval of short scientific texts (1993)
0.01
0.0074937996 = product of:
0.052456595 = sum of:
0.010089659 = weight(_text_:information in 2715) [ClassicSimilarity], result of:
0.010089659 = score(doc=2715,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.19395474 = fieldWeight in 2715, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.078125 = fieldNorm(doc=2715)
0.042366937 = weight(_text_:retrieval in 2715) [ClassicSimilarity], result of:
0.042366937 = score(doc=2715,freq=4.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.47264296 = fieldWeight in 2715, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.078125 = fieldNorm(doc=2715)
0.14285715 = coord(2/14)
- Abstract
- A conceptual model for integrating short scientific texts is described, which extends classical text storage and retrieval. A brief comparison with related approaches (such as case-based reasoning and classification-based reasoning) is also provided
- Source
- Information processing and management. 29(1993) no.2, S.209-214
-
Akerele, O.; David, A.; Osofisan, A.: Using the concepts of Case Based Reasoning and Basic Categories for enhancing adaptation to the user's level of knowledge in Decision Support System (2014)
0.01
0.0068696537 = product of:
0.032058384 = sum of:
0.0060537956 = weight(_text_:information in 1449) [ClassicSimilarity], result of:
0.0060537956 = score(doc=1449,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.116372846 = fieldWeight in 1449, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=1449)
0.01797477 = weight(_text_:retrieval in 1449) [ClassicSimilarity], result of:
0.01797477 = score(doc=1449,freq=2.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.20052543 = fieldWeight in 1449, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=1449)
0.008029819 = product of:
0.024089456 = sum of:
0.024089456 = weight(_text_:22 in 1449) [ClassicSimilarity], result of:
0.024089456 = score(doc=1449,freq=2.0), product of:
0.103770934 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.029633347 = queryNorm
0.23214069 = fieldWeight in 1449, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=1449)
0.33333334 = coord(1/3)
0.21428572 = coord(3/14)
- Abstract
- In most search systems, mapping queries with documents employs techniques such as vector space model, naïve Bayes, Bayesian theorem etc. to classify resulting documents. In this research studies, we are proposing the use of the concept of basic categories to representing the user's level of knowledge based on the concepts he employed during his search activities, so that the system could propose adapted results based on the observed user's level of knowledge. Our hypothesis is that this approach will enhance the decision support system for solving decisional problems in which information retrieval constitutes the backbone technical problem.
- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
-
Pfeffer, M.: Automatische Vergabe von RVK-Notationen mittels fallbasiertem Schließen (2009)
0.01
0.005877295 = product of:
0.041141063 = sum of:
0.033111244 = weight(_text_:bibliothek in 3051) [ClassicSimilarity], result of:
0.033111244 = score(doc=3051,freq=2.0), product of:
0.121660605 = queryWeight, product of:
4.1055303 = idf(docFreq=1980, maxDocs=44218)
0.029633347 = queryNorm
0.27216077 = fieldWeight in 3051, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.1055303 = idf(docFreq=1980, maxDocs=44218)
0.046875 = fieldNorm(doc=3051)
0.008029819 = product of:
0.024089456 = sum of:
0.024089456 = weight(_text_:22 in 3051) [ClassicSimilarity], result of:
0.024089456 = score(doc=3051,freq=2.0), product of:
0.103770934 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.029633347 = queryNorm
0.23214069 = fieldWeight in 3051, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=3051)
0.33333334 = coord(1/3)
0.14285715 = coord(2/14)
- Abstract
- Klassifikation von bibliografischen Einheiten ist für einen systematischen Zugang zu den Beständen einer Bibliothek und deren Aufstellung unumgänglich. Bislang wurde diese Aufgabe von Fachexperten manuell erledigt, sei es individuell nach einer selbst entwickelten Systematik oder kooperativ nach einer gemeinsamen Systematik. In dieser Arbeit wird ein Verfahren zur Automatisierung des Klassifikationsvorgangs vorgestellt. Dabei kommt das Verfahren des fallbasierten Schließens zum Einsatz, das im Kontext der Forschung zur künstlichen Intelligenz entwickelt wurde. Das Verfahren liefert für jedes Werk, für das bibliografische Daten vorliegen, eine oder mehrere mögliche Klassifikationen. In Experimenten werden die Ergebnisse der automatischen Klassifikation mit der durch Fachexperten verglichen. Diese Experimente belegen die hohe Qualität der automatischen Klassifikation und dass das Verfahren geeignet ist, Fachexperten bei der Klassifikationsarbeit signifikant zu entlasten. Auch die nahezu vollständige Resystematisierung eines Bibliothekskataloges ist - mit gewissen Abstrichen - möglich.
- Date
- 22. 8.2009 19:51:28
-
Rissland, E.L.; Daniels, J.J.: ¬The synergistic application of CBR to IR (1996)
0.01
0.005670654 = product of:
0.039694577 = sum of:
0.00856136 = weight(_text_:information in 7736) [ClassicSimilarity], result of:
0.00856136 = score(doc=7736,freq=4.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.16457605 = fieldWeight in 7736, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=7736)
0.031133216 = weight(_text_:retrieval in 7736) [ClassicSimilarity], result of:
0.031133216 = score(doc=7736,freq=6.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.34732026 = fieldWeight in 7736, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=7736)
0.14285715 = coord(2/14)
- Abstract
- Discusses a hybrid approach combining case-based reasoning and information retrieval for the retrieval of full text documents. It takes as input a standard symbolic representation of a problem case and retrieves text of relevant cases from a document collection dramatically larger than the case base available to the CBR system. It works by performing a standard HYPO style analysis and uses the texts associated with important classes of cases found in this analysis to seed a modified version of INQUERY's relevance feedback mechanism in order to generate a query composed of individual terms or pairs of terms. It exteds the reach of CBR to much larger corpora, and it anbales the injection of knowledge based techniques into traditional IR. Describes the CBR-IR approach and reports on-going experiments
- Footnote
- Contribution to a special issue on the application of artificial intelligence to information retrieval
-
Pfeffer, M.: Automatische Vergabe von RVK-Notationen anhand von bibliografischen Daten mittels fallbasiertem Schließen (2007)
0.01
0.0055950056 = product of:
0.03916504 = sum of:
0.033111244 = weight(_text_:bibliothek in 558) [ClassicSimilarity], result of:
0.033111244 = score(doc=558,freq=2.0), product of:
0.121660605 = queryWeight, product of:
4.1055303 = idf(docFreq=1980, maxDocs=44218)
0.029633347 = queryNorm
0.27216077 = fieldWeight in 558, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.1055303 = idf(docFreq=1980, maxDocs=44218)
0.046875 = fieldNorm(doc=558)
0.0060537956 = weight(_text_:information in 558) [ClassicSimilarity], result of:
0.0060537956 = score(doc=558,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.116372846 = fieldWeight in 558, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=558)
0.14285715 = coord(2/14)
- Abstract
- Klassifikation von bibliografischen Einheiten ist für einen systematischen Zugang zu den Beständen einer Bibliothek und deren Aufstellung unumgänglich. Bislang wurde diese Aufgabe von Fachexperten manuell erledigt, sei es individuell nach einer selbst entwickelten Systematik oder kooperativ nach einer gemeinsamen Systematik. In dieser Arbeit wird ein Verfahren zur Automatisierung des Klassifikationsvorgangs vorgestellt. Dabei kommt das Verfahren des fallbasierten Schließens zum Einsatz, das im Kontext der Forschung zur künstlichen Intelligenz entwickelt wurde. Das Verfahren liefert für jedes Werk, für das bibliografische Daten vorliegen, eine oder mehrere mögliche Klassifikationen. In Experimenten werden die Ergebnisse der automatischen Klassifikation mit der durch Fachexperten verglichen. Diese Experimente belegen die hohe Qualität der automatischen Klassifikation und dass das Verfahren geeignet ist, Fachexperten bei der Klassifikationsarbeit signifikant zu entlasten. Auch die nahezu vollständige Resystematisierung eines Bibliothekskataloges ist - mit gewissen Abstrichen - möglich.
- Content
- Masterarbeit im Rahmen des postgradualen Fernstudiums Master of Arts (Library and Information Science)
-
He, W.; Erdelez, S.; Wang, F.-K.; Shyu, C.-R.: ¬The effects of conceptual description and search practice on users' mental models and information seeking in a case-based reasoning retrieval system (2008)
0.00
0.004954607 = product of:
0.034682248 = sum of:
0.008737902 = weight(_text_:information in 2036) [ClassicSimilarity], result of:
0.008737902 = score(doc=2036,freq=6.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.16796975 = fieldWeight in 2036, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=2036)
0.025944345 = weight(_text_:retrieval in 2036) [ClassicSimilarity], result of:
0.025944345 = score(doc=2036,freq=6.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.28943354 = fieldWeight in 2036, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=2036)
0.14285715 = coord(2/14)
- Abstract
- This paper reportes a study that investigated the effects of conceptual description and search practice on users' mental models and information seeking in a case-based reasoning retrieval (CBR) system with a best match search mechanism. This study also found examined how the presence of a mental model affects the users' search performance and satisfaction in this system. The results of this study revealed that the conceptual description and search practice treatments do not have significantly different effects on the types of user's mental models, search correctness, and search satisfaction. However, the search practice group spent significantly less time than the conceptual description group in finding the results. Qualitative analysis for the subjects' post mental models revealed that subjects in the conceptual description group seem to have more complete mental models of the best match system than those in the search practice group. This study also that subjects with the best match mental models have significantly higher search correctness and search result satisfaction than subjects without the best match mental models. However, the best match mental models do not guarantee less search time in finding the results. This study did not find a significant correlation among search time, search correctness and search satisfaction. The study concludes with suggestions for future research and implications for system developers who are interested in CBR retrieval systems.
- Source
- Information processing and management. 44(2008) no.1, S.294-309
-
Löckenhoff, H.: Case-Based Teaching/Learning for issue orientation and control (1996)
0.00
0.0032137486 = product of:
0.044992477 = sum of:
0.044992477 = weight(_text_:wide in 5205) [ClassicSimilarity], result of:
0.044992477 = score(doc=5205,freq=2.0), product of:
0.1312982 = queryWeight, product of:
4.4307585 = idf(docFreq=1430, maxDocs=44218)
0.029633347 = queryNorm
0.342674 = fieldWeight in 5205, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.4307585 = idf(docFreq=1430, maxDocs=44218)
0.0546875 = fieldNorm(doc=5205)
0.071428575 = coord(1/14)
- Abstract
- Case Based Reasoning (CBR) is discussed in connection with a wide variety of knowledge aspects. Obviously knowledge acquisition under conditions of rapid and increasingly disruptive change will necessarily rely on the proper use of case experience. The following remarks emerged from practice oriented teaching/learning in the domians of social sciences, practical philosophy, didactics and epistemology. The main interest will be directed to methodical concepts of knowledge transfer, in particular to didactics and learning within the teaching/learning system
-
Kolodner, J.: Case-based reasoning (1993)
0.00
0.002420968 = product of:
0.033893548 = sum of:
0.033893548 = weight(_text_:retrieval in 526) [ClassicSimilarity], result of:
0.033893548 = score(doc=526,freq=4.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.37811437 = fieldWeight in 526, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0625 = fieldNorm(doc=526)
0.071428575 = coord(1/14)
- Content
- Pt.1: Background: waht is CBR? Case studies of several case-based reasoners. Reasoning using cases. The cognitive model. Pt.2: The case library: representing and indexing cases. Indexing vocabulary. Methods for index selection. Pt.3: Retrieving cases from the case library. Organizational structures and retrieval algorithms. Matching and ranking cases. Indexing and retrieval. Pt.4: Using cases. Adaptation methods and strategies. Controlling adaptation. Using cases for interpretation and evaluation. Pt.5: Pulling it all together. Building a case-based reasoner. Conclusions, opportunities, challenges. Appendix: A case library of case-based reasoning systems
-
Mazzucchelli, A.; Sartori , F.: String similarity in CBR platforms : a preliminary study (2014)
0.00
0.0023472693 = product of:
0.016430885 = sum of:
0.0070627616 = weight(_text_:information in 1568) [ClassicSimilarity], result of:
0.0070627616 = score(doc=1568,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.13576832 = fieldWeight in 1568, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0546875 = fieldNorm(doc=1568)
0.009368123 = product of:
0.028104367 = sum of:
0.028104367 = weight(_text_:22 in 1568) [ClassicSimilarity], result of:
0.028104367 = score(doc=1568,freq=2.0), product of:
0.103770934 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.029633347 = queryNorm
0.2708308 = fieldWeight in 1568, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=1568)
0.33333334 = coord(1/3)
0.14285715 = coord(2/14)
- Pages
- S.22-29
- Series
- Communications in computer and information science; 478
-
Mataras, R.L.D.; Plaza, E.: Case-based reasoning : an overview (1997)
0.00
0.0021398535 = product of:
0.029957948 = sum of:
0.029957948 = weight(_text_:retrieval in 436) [ClassicSimilarity], result of:
0.029957948 = score(doc=436,freq=2.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.33420905 = fieldWeight in 436, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.078125 = fieldNorm(doc=436)
0.071428575 = coord(1/14)
- Abstract
- Gives an overview of CBR with emphasis on European ctivites in the field. Identifies major open problems of CBR associated with: retrieval/selection, memory organization, matching, adaptation/evaluation, forgetting and integration with other techniques
-
Golding, A.R.; Rosenbloom, P.S.: Improving accuracy by combining rule-based and case-based reasoning (1996)
0.00
7.6474476E-4 = product of:
0.010706427 = sum of:
0.010706427 = product of:
0.032119278 = sum of:
0.032119278 = weight(_text_:22 in 607) [ClassicSimilarity], result of:
0.032119278 = score(doc=607,freq=2.0), product of:
0.103770934 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.029633347 = queryNorm
0.30952093 = fieldWeight in 607, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=607)
0.33333334 = coord(1/3)
0.071428575 = coord(1/14)
- Date
- 6. 3.1997 16:22:15
-
Ram, A.; Santamaria, J.C.: Continuous case-based reasoning (1997)
0.00
7.6474476E-4 = product of:
0.010706427 = sum of:
0.010706427 = product of:
0.032119278 = sum of:
0.032119278 = weight(_text_:22 in 435) [ClassicSimilarity], result of:
0.032119278 = score(doc=435,freq=2.0), product of:
0.103770934 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.029633347 = queryNorm
0.30952093 = fieldWeight in 435, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=435)
0.33333334 = coord(1/3)
0.071428575 = coord(1/14)
- Date
- 6. 3.1997 16:22:15
-
Kohno, T.: Error repair and knowledge acquisition via case-based reasoning (1997)
0.00
7.6474476E-4 = product of:
0.010706427 = sum of:
0.010706427 = product of:
0.032119278 = sum of:
0.032119278 = weight(_text_:22 in 437) [ClassicSimilarity], result of:
0.032119278 = score(doc=437,freq=2.0), product of:
0.103770934 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.029633347 = queryNorm
0.30952093 = fieldWeight in 437, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=437)
0.33333334 = coord(1/3)
0.071428575 = coord(1/14)
- Date
- 6. 3.1997 16:22:15
-
Althoff, K.-D.; Wess, S.; Manago, M.; Bergmann, R.; Maurer, F.; Auriol, E.; Conruyt, N.; Traphöner, R.; Bräuer, M.; Dittrich, S.: Induction and case-based reasoning for classification tasks (1994)
0.00
5.04483E-4 = product of:
0.0070627616 = sum of:
0.0070627616 = weight(_text_:information in 7744) [ClassicSimilarity], result of:
0.0070627616 = score(doc=7744,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.13576832 = fieldWeight in 7744, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0546875 = fieldNorm(doc=7744)
0.071428575 = coord(1/14)
- Source
- Information systems and data analysis: prospects - foundations - applications. Proc. of the 17th Annual Conference of the Gesellschaft für Klassifikation, Kaiserslautern, March 3-5, 1993. Ed.: H.-H. Bock et al
-
Analogie in der Wissensrepräsentation: Case-Based Reasoning und räumliche Modelle : 4. Tagung der deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Trier, 17.-20. Oktober 1995 (1996)
0.00
3.6034497E-4 = product of:
0.0050448296 = sum of:
0.0050448296 = weight(_text_:information in 5201) [ClassicSimilarity], result of:
0.0050448296 = score(doc=5201,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.09697737 = fieldWeight in 5201, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.0390625 = fieldNorm(doc=5201)
0.071428575 = coord(1/14)
- Abstract
- Enthält die Beiträge: CZAP, H.: Einführung in die Wissensorganisation und Case-Based Reasoning (CBR); ALTHOFF, K.-D., R. TRAPHÖNER u. S. WESS: Efficient integration on induction and Case-Base Reasoning: the INRECA System; SCHIEMANN, I. u. A. WOLTERING: Fallspeicherorganisation in der CBR-Shell Janus; COULON, C.-H.: Die Rolle des Anpassungswissens im CBR (Am Beispiel der Ausnutzung von Struktur im CBR); SCHAAF, J.W.: Fischen und Versenken: ein anytime-Algorithmus zur Suche nach situationsgerechten Fällen; JAENECKE, P.: Erkenntnistheoretische Untersuchungen über fallbezogenes Schlußfolgern; LÖCKENHOFF, H.: Cabse-Based Teaching/Learning for issue orientation and control; BIES, W.: 'Denken in Bildern': zu den Metaphern der Wissensorganisation; PRIBBENOW, S.: Räumliches Wissen: zur Interaktion von Logik und Bildern; STOLLE, M. u. V. KIRCHBERG: Mental maps in der Stadtforschung: Grundlage und Perspektiven; BAYER, H. u. R. BAUEREISS: Der Familienatlas als sozialräumliche Information; HARDT, F., G. TASSOUKIS u. H.P. OHLY: Räumliche Hintergrundinformation in bibliographischen Datenbanken; SALENTIN, K.: Geodemographische Ansätze beim Sampling im Direktmarketingverfahren; PIERAU, K., G. NARWELEIT u. H. THÜMMLER: Entwicklung eines Geographisch-Historischen Informationssystems; LENSKI, W. u. E. WETTE-ROCH: Terminologie und Wissensrepräsentation in pragmatischer Sichtweise; FUGMANN, R.: Die Entlineaririserung und Strukturierung von Texten zur Inhaltserschließung und Wissensrepräsentation; LORENZ, B.: Überlegungen zur Verbundklassifikation; NACKE, O.: Ein einfaches Verfahren zur Analyse großer Wissensmengen; BOL, G., E. HOTZ u. T. STÜTZLE: Neuronale Netze zur Klassifikation von Fehlrern in der statistischen Prozeßregulierung
