Lund, K.; Burgess, C.; Atchley, R.A.: Semantic and associative priming in high-dimensional semantic space (1995)
0.00
0.004334098 = product of:
0.030338686 = sum of:
0.020970564 = weight(_text_:retrieval in 2151) [ClassicSimilarity], result of:
0.020970564 = score(doc=2151,freq=2.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.23394634 = fieldWeight in 2151, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=2151)
0.009368123 = product of:
0.028104367 = sum of:
0.028104367 = weight(_text_:22 in 2151) [ClassicSimilarity], result of:
0.028104367 = score(doc=2151,freq=2.0), product of:
0.103770934 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.029633347 = queryNorm
0.2708308 = fieldWeight in 2151, 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=2151)
0.33333334 = coord(1/3)
0.14285715 = coord(2/14)
- Source
- Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society: July 22 - 25, 1995, University of Pittsburgh / ed. by Johanna D. Moore and Jill Fain Lehmann
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
Lund, K.; Burgess, C.: Producing high-dimensional semantic spaces from lexical co-occurrence (1996)
0.00
0.00406575 = product of:
0.028460251 = sum of:
0.0104854815 = weight(_text_:information in 1704) [ClassicSimilarity], result of:
0.0104854815 = score(doc=1704,freq=6.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.20156369 = fieldWeight in 1704, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=1704)
0.01797477 = weight(_text_:retrieval in 1704) [ClassicSimilarity], result of:
0.01797477 = score(doc=1704,freq=2.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.20052543 = fieldWeight in 1704, 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=1704)
0.14285715 = coord(2/14)
- Abstract
- A procedure that processes a corpus of text and produces numeric vectors containing information about its meanings for each word is presented. This procedure is applied to a large corpus of natural language text taken from Usenet, and the resulting vectors are examined to determine what information is contained within them. These vectors provide the coordinates in a high-dimensional space in which word relationships can be analyzed. Analyses of both vector similarity and multidimensional scaling demonstrate that there is significant semantic information carried in the vectors. A comparison of vector similarity with human reaction times in a single-word priming experiment is presented. These vectors provide the basis for a representational model of semantic memory, hyperspace analogue to language (HAL).
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval