-
Chen, L.; Zeng, J.; Tokuda, N.: ¬A "stereo" document representation for textual information retrieval (2006)
0.02
0.018255439 = product of:
0.045638595 = sum of:
0.026986076 = weight(_text_:technology in 5292) [ClassicSimilarity], result of:
0.026986076 = score(doc=5292,freq=2.0), product of:
0.13667917 = queryWeight, product of:
2.978387 = idf(docFreq=6114, maxDocs=44218)
0.04589033 = queryNorm
0.19744103 = fieldWeight in 5292, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.978387 = idf(docFreq=6114, maxDocs=44218)
0.046875 = fieldNorm(doc=5292)
0.01865252 = product of:
0.03730504 = sum of:
0.03730504 = weight(_text_:22 in 5292) [ClassicSimilarity], result of:
0.03730504 = score(doc=5292,freq=2.0), product of:
0.16070013 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04589033 = queryNorm
0.23214069 = fieldWeight in 5292, 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=5292)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Date
- 22. 7.2006 17:33:43
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.768-774
-
Xie, H.; Li, X.; Wang, T.; Lau, R.Y.K.; Wong, T.-L.; Chen, L.; Wang, F.L.; Li, Q.: Incorporating sentiment into tag-based user profiles and resource profiles for personalized search in folksonomy (2016)
0.01
0.0064496296 = product of:
0.032248147 = sum of:
0.032248147 = weight(_text_:social in 2671) [ClassicSimilarity], result of:
0.032248147 = score(doc=2671,freq=2.0), product of:
0.18299131 = queryWeight, product of:
3.9875789 = idf(docFreq=2228, maxDocs=44218)
0.04589033 = queryNorm
0.17622775 = fieldWeight in 2671, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.9875789 = idf(docFreq=2228, maxDocs=44218)
0.03125 = fieldNorm(doc=2671)
0.2 = coord(1/5)
- Footnote
- Beitrag in einem Themenheft "Emotion and sentiment in social and expressive media"
-
Chen, L.; Holsapple, C.W.; Hsiao, S.-H.; Ke, Z.; Oh, J.-Y.; Yang, Z.: Knowledge-dissemination channels : analytics of stature evaluation (2017)
0.00
0.0044976794 = product of:
0.022488397 = sum of:
0.022488397 = weight(_text_:technology in 3531) [ClassicSimilarity], result of:
0.022488397 = score(doc=3531,freq=2.0), product of:
0.13667917 = queryWeight, product of:
2.978387 = idf(docFreq=6114, maxDocs=44218)
0.04589033 = queryNorm
0.16453418 = fieldWeight in 3531, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.978387 = idf(docFreq=6114, maxDocs=44218)
0.0390625 = fieldNorm(doc=3531)
0.2 = coord(1/5)
- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.4, S.911-930
-
Chen, L.; Fang, H.: ¬An automatic method for ex-tracting innovative ideas based on the Scopus® database (2019)
0.00
0.0044976794 = product of:
0.022488397 = sum of:
0.022488397 = weight(_text_:technology in 5310) [ClassicSimilarity], result of:
0.022488397 = score(doc=5310,freq=2.0), product of:
0.13667917 = queryWeight, product of:
2.978387 = idf(docFreq=6114, maxDocs=44218)
0.04589033 = queryNorm
0.16453418 = fieldWeight in 5310, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.978387 = idf(docFreq=6114, maxDocs=44218)
0.0390625 = fieldNorm(doc=5310)
0.2 = coord(1/5)
- Abstract
- The novelty of knowledge claims in a research paper can be considered an evaluation criterion for papers to supplement citations. To provide a foundation for research evaluation from the perspective of innovativeness, we propose an automatic approach for extracting innovative ideas from the abstracts of technology and engineering papers. The approach extracts N-grams as candidates based on part-of-speech tagging and determines whether they are novel by checking the Scopus® database to determine whether they had ever been presented previously. Moreover, we discussed the distributions of innovative ideas in different abstract structures. To improve the performance by excluding noisy N-grams, a list of stopwords and a list of research description characteristics were developed. We selected abstracts of articles published from 2011 to 2017 with the topic of semantic analysis as the experimental texts. Excluding noisy N-grams, considering the distribution of innovative ideas in abstracts, and suitably combining N-grams can effectively improve the performance of automatic innovative idea extraction. Unlike co-word and co-citation analysis, innovative-idea extraction aims to identify the differences in a paper from all previously published papers.
-
Chen, L.; Ding, J.; Larivière, V.: Measuring the citation context of national self-references : how a web journal club is used (2022)
0.00
0.0044976794 = product of:
0.022488397 = sum of:
0.022488397 = weight(_text_:technology in 545) [ClassicSimilarity], result of:
0.022488397 = score(doc=545,freq=2.0), product of:
0.13667917 = queryWeight, product of:
2.978387 = idf(docFreq=6114, maxDocs=44218)
0.04589033 = queryNorm
0.16453418 = fieldWeight in 545, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.978387 = idf(docFreq=6114, maxDocs=44218)
0.0390625 = fieldNorm(doc=545)
0.2 = coord(1/5)
- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.5, S.671-686
-
Tang, X.; Chen, L.; Cui, J.; Wei, B.: Knowledge representation learning with entity descriptions, hierarchical types, and textual relations (2019)
0.00
0.0037305038 = product of:
0.01865252 = sum of:
0.01865252 = product of:
0.03730504 = sum of:
0.03730504 = weight(_text_:22 in 5101) [ClassicSimilarity], result of:
0.03730504 = score(doc=5101,freq=2.0), product of:
0.16070013 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04589033 = queryNorm
0.23214069 = fieldWeight in 5101, 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=5101)
0.5 = coord(1/2)
0.2 = coord(1/5)
- Date
- 17. 3.2019 13:22:53
