Temporal semantic analysis of conference proceedings
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 10193 LNCS, Page: 762-765
2017
- 1Citations
- 11Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
T-RecS is a system which implements several computational linguistic techniques for analyzing word usage variations over time periods in a document collection. We analyzed ACM RecSys conference proceedings from the first edition held in 2007, to the one held in 2015. The idea is to identify linguistic phenomena that reflect some interesting variations for the research community, such as a topic shift, or how the correlation between two terms changed over the time, or how the similarity between two authors evolved over time.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85018708552&origin=inward; http://dx.doi.org/10.1007/978-3-319-56608-5_78; http://link.springer.com/10.1007/978-3-319-56608-5_78; http://link.springer.com/content/pdf/10.1007/978-3-319-56608-5_78; https://dx.doi.org/10.1007/978-3-319-56608-5_78; https://link.springer.com/chapter/10.1007/978-3-319-56608-5_78
Springer Science and Business Media LLC
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