Performance Analysis of Multilevel Indices for Service Repositories
Proceedings - 2016 12th International Conference on Semantics, Knowledge and Grids, SKG 2016, Page: 103-108
2017
- 1Citations
- 3Usage
- 2Captures
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.
Metrics Details
- Citations1
- Citation Indexes1
- CrossRef1
- Usage3
- Abstract Views3
- Captures2
- Readers2
Conference Paper Description
There are many different index structures for servicerepositories, such as sequential index, inverted index and multilevelindices that includes three deployments. Different servicesets maybe have different characteristics that may affect performancefrom different aspects. What characteristic could affectretrieval performance? How to select an optimal storage structurefor a given service set? To address these issues, this paperanalyses five indexing models and proposes expectation of traversedservice count to estimate performance of service retrieval. The proposed expectation formulas of five indices reveal whatdifferent characteristics of a service set could affect its retrievalperformance for different indices. Experimental results validatecorrectness of the proposed formulas.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85013322072&origin=inward; http://dx.doi.org/10.1109/skg.2016.023; http://ieeexplore.ieee.org/document/7815084/; http://xplorestaging.ieee.org/ielx7/7814390/7815062/07815084.pdf?arnumber=7815084; https://scholarworks.boisestate.edu/cs_facpubs/142; https://scholarworks.boisestate.edu/cgi/viewcontent.cgi?article=1147&context=cs_facpubs
Institute of Electrical and Electronics Engineers (IEEE)
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know