-
Chen, M.; Liu, X.; Qin, J.: Semantic relation extraction from socially-generated tags : a methodology for metadata generation (2008)
0.02
0.018435527 = product of:
0.036871053 = sum of:
0.036871053 = product of:
0.055306576 = sum of:
0.024974043 = weight(_text_:j in 2648) [ClassicSimilarity], result of:
0.024974043 = score(doc=2648,freq=2.0), product of:
0.14227505 = queryWeight, product of:
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.044775832 = queryNorm
0.17553353 = fieldWeight in 2648, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.0390625 = fieldNorm(doc=2648)
0.030332536 = weight(_text_:22 in 2648) [ClassicSimilarity], result of:
0.030332536 = score(doc=2648,freq=2.0), product of:
0.15679733 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.044775832 = queryNorm
0.19345059 = fieldWeight in 2648, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=2648)
0.6666667 = coord(2/3)
0.5 = coord(1/2)
- Source
- Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
-
Liu, X.; Croft, W.B.: Statistical language modeling for information retrieval (2004)
0.01
0.01083854 = product of:
0.02167708 = sum of:
0.02167708 = product of:
0.06503124 = sum of:
0.06503124 = weight(_text_:n in 4277) [ClassicSimilarity], result of:
0.06503124 = score(doc=4277,freq=4.0), product of:
0.19305801 = queryWeight, product of:
4.3116565 = idf(docFreq=1611, maxDocs=44218)
0.044775832 = queryNorm
0.33684817 = fieldWeight in 4277, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
4.3116565 = idf(docFreq=1611, maxDocs=44218)
0.0390625 = fieldNorm(doc=4277)
0.33333334 = coord(1/3)
0.5 = coord(1/2)
- Abstract
- This chapter reviews research and applications in statistical language modeling for information retrieval (IR), which has emerged within the past several years as a new probabilistic framework for describing information retrieval processes. Generally speaking, statistical language modeling, or more simply language modeling (LM), involves estimating a probability distribution that captures statistical regularities of natural language use. Applied to information retrieval, language modeling refers to the problem of estimating the likelihood that a query and a document could have been generated by the same language model, given the language model of the document either with or without a language model of the query. The roots of statistical language modeling date to the beginning of the twentieth century when Markov tried to model letter sequences in works of Russian literature (Manning & Schütze, 1999). Zipf (1929, 1932, 1949, 1965) studied the statistical properties of text and discovered that the frequency of works decays as a Power function of each works rank. However, it was Shannon's (1951) work that inspired later research in this area. In 1951, eager to explore the applications of his newly founded information theory to human language, Shannon used a prediction game involving n-grams to investigate the information content of English text. He evaluated n-gram models' performance by comparing their crossentropy an texts with the true entropy estimated using predictions made by human subjects. For many years, statistical language models have been used primarily for automatic speech recognition. Since 1980, when the first significant language model was proposed (Rosenfeld, 2000), statistical language modeling has become a fundamental component of speech recognition, machine translation, and spelling correction.
-
Clewley, N.; Chen, S.Y.; Liu, X.: Cognitive styles and search engine preferences : field dependence/independence vs holism/serialism (2010)
0.01
0.0076640043 = product of:
0.015328009 = sum of:
0.015328009 = product of:
0.045984026 = sum of:
0.045984026 = weight(_text_:n in 3961) [ClassicSimilarity], result of:
0.045984026 = score(doc=3961,freq=2.0), product of:
0.19305801 = queryWeight, product of:
4.3116565 = idf(docFreq=1611, maxDocs=44218)
0.044775832 = queryNorm
0.23818761 = fieldWeight in 3961, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.3116565 = idf(docFreq=1611, maxDocs=44218)
0.0390625 = fieldNorm(doc=3961)
0.33333334 = coord(1/3)
0.5 = coord(1/2)
-
Liu, X.; Bu, Y.; Li, M.; Li, J.: Monodisciplinary collaboration disrupts science more than multidisciplinary collaboration (2024)
0.00
0.0049948087 = product of:
0.009989617 = sum of:
0.009989617 = product of:
0.029968852 = sum of:
0.029968852 = weight(_text_:j in 1202) [ClassicSimilarity], result of:
0.029968852 = score(doc=1202,freq=2.0), product of:
0.14227505 = queryWeight, product of:
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.044775832 = queryNorm
0.21064025 = fieldWeight in 1202, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.046875 = fieldNorm(doc=1202)
0.33333334 = coord(1/3)
0.5 = coord(1/2)
-
Liu, X.; Zhang, J.; Guo, C.: Full-text citation analysis : a new method to enhance scholarly networks (2013)
0.00
0.0041623404 = product of:
0.008324681 = sum of:
0.008324681 = product of:
0.024974043 = sum of:
0.024974043 = weight(_text_:j in 1044) [ClassicSimilarity], result of:
0.024974043 = score(doc=1044,freq=2.0), product of:
0.14227505 = queryWeight, product of:
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.044775832 = queryNorm
0.17553353 = fieldWeight in 1044, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.0390625 = fieldNorm(doc=1044)
0.33333334 = coord(1/3)
0.5 = coord(1/2)
-
Liu, X.; Qin, J.: ¬An interactive metadata model for structural, descriptive, and referential representation of scholarly output (2014)
0.00
0.0041623404 = product of:
0.008324681 = sum of:
0.008324681 = product of:
0.024974043 = sum of:
0.024974043 = weight(_text_:j in 1253) [ClassicSimilarity], result of:
0.024974043 = score(doc=1253,freq=2.0), product of:
0.14227505 = queryWeight, product of:
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.044775832 = queryNorm
0.17553353 = fieldWeight in 1253, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.0390625 = fieldNorm(doc=1253)
0.33333334 = coord(1/3)
0.5 = coord(1/2)
-
Chen, Z.; Huang, Y.; Tian, J.; Liu, X.; Fu, K.; Huang, T.: Joint model for subsentence-level sentiment analysis with Markov logic (2015)
0.00
0.0041623404 = product of:
0.008324681 = sum of:
0.008324681 = product of:
0.024974043 = sum of:
0.024974043 = weight(_text_:j in 2210) [ClassicSimilarity], result of:
0.024974043 = score(doc=2210,freq=2.0), product of:
0.14227505 = queryWeight, product of:
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.044775832 = queryNorm
0.17553353 = fieldWeight in 2210, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.0390625 = fieldNorm(doc=2210)
0.33333334 = coord(1/3)
0.5 = coord(1/2)
-
Liu, X.; Hu, M.; Xiao, B.S.; Shao, J.: Is my doctor around me? : Investigating the impact of doctors' presence on patients' review behaviors on an online health platform (2022)
0.00
0.0041623404 = product of:
0.008324681 = sum of:
0.008324681 = product of:
0.024974043 = sum of:
0.024974043 = weight(_text_:j in 650) [ClassicSimilarity], result of:
0.024974043 = score(doc=650,freq=2.0), product of:
0.14227505 = queryWeight, product of:
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.044775832 = queryNorm
0.17553353 = fieldWeight in 650, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.0390625 = fieldNorm(doc=650)
0.33333334 = coord(1/3)
0.5 = coord(1/2)
