-
Srihari, R.K.: Using speech input for image interpretation, annotation, and retrieval (1997)
0.02
0.017311653 = product of:
0.051934958 = sum of:
0.03489179 = weight(_text_:b in 764) [ClassicSimilarity], result of:
0.03489179 = score(doc=764,freq=2.0), product of:
0.14855953 = queryWeight, product of:
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.041930884 = queryNorm
0.23486741 = fieldWeight in 764, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.046875 = fieldNorm(doc=764)
0.017043166 = product of:
0.03408633 = sum of:
0.03408633 = weight(_text_:22 in 764) [ClassicSimilarity], result of:
0.03408633 = score(doc=764,freq=2.0), product of:
0.1468348 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041930884 = queryNorm
0.23214069 = fieldWeight in 764, 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=764)
0.5 = coord(1/2)
0.33333334 = coord(2/6)
- Date
- 22. 9.1997 19:16:05
- Source
- Digital image access and retrieval: Proceedings of the 1996 Clinic on Library Applications of Data Processing, 24-26 Mar 1996. Ed.: P.B. Heidorn u. B. Sandore
-
Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002)
0.01
0.0058152988 = product of:
0.03489179 = sum of:
0.03489179 = weight(_text_:b in 1850) [ClassicSimilarity], result of:
0.03489179 = score(doc=1850,freq=2.0), product of:
0.14855953 = queryWeight, product of:
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.041930884 = queryNorm
0.23486741 = fieldWeight in 1850, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.046875 = fieldNorm(doc=1850)
0.16666667 = coord(1/6)
-
Galitsky, B.: Can many agents answer questions better than one? (2005)
0.01
0.0058152988 = product of:
0.03489179 = sum of:
0.03489179 = weight(_text_:b in 3094) [ClassicSimilarity], result of:
0.03489179 = score(doc=3094,freq=2.0), product of:
0.14855953 = queryWeight, product of:
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.041930884 = queryNorm
0.23486741 = fieldWeight in 3094, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.046875 = fieldNorm(doc=3094)
0.16666667 = coord(1/6)
-
Lin, J.; Katz, B.: Building a reusable test collection for question answering (2006)
0.01
0.0058152988 = product of:
0.03489179 = sum of:
0.03489179 = weight(_text_:b in 5045) [ClassicSimilarity], result of:
0.03489179 = score(doc=5045,freq=2.0), product of:
0.14855953 = queryWeight, product of:
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.041930884 = queryNorm
0.23486741 = fieldWeight in 5045, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.046875 = fieldNorm(doc=5045)
0.16666667 = coord(1/6)
-
Rösener, C.: ¬Die Stecknadel im Heuhaufen : Natürlichsprachlicher Zugang zu Volltextdatenbanken (2005)
0.00
0.0038768656 = product of:
0.023261193 = sum of:
0.023261193 = weight(_text_:b in 548) [ClassicSimilarity], result of:
0.023261193 = score(doc=548,freq=2.0), product of:
0.14855953 = queryWeight, product of:
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.041930884 = queryNorm
0.15657827 = fieldWeight in 548, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.542962 = idf(docFreq=3476, maxDocs=44218)
0.03125 = fieldNorm(doc=548)
0.16666667 = coord(1/6)
- Content
- 5: Interaktion 5.1 Frage-Antwort- bzw. Dialogsysteme: Forschungen und Projekte 5.2 Darstellung und Visualisierung von Wissen 5.3 Das Dialogsystem im Rahmen des LeWi-Projektes 5.4 Ergebnisdarstellung und Antwortpräsentation im LeWi-Kontext 6: Testumgebungen und -ergebnisse 7: Ergebnisse und Ausblick 7.1 Ausgangssituation 7.2 Schlussfolgerungen 7.3 Ausblick Anhang A Auszüge aus der Grob- bzw. Feinklassifikation des BMM Anhang B MPRO - Formale Beschreibung der wichtigsten Merkmale ... Anhang C Fragentypologie mit Beispielsätzen (Auszug) Anhang D Semantische Merkmale im morphologischen Lexikon (Auszug) Anhang E Regelbeispiele für die Fragentypzuweisung Anhang F Aufstellung der möglichen Suchen im LeWi-Dialogmodul (Auszug) Anhang G Vollständiger Dialogbaum zu Beginn des Projektes Anhang H Statuszustände zur Ermittlung der Folgefragen (Auszug)
