SMS spam filtering: Methods and data
Expert Systems with Applications, ISSN: 0957-4174, Vol: 39, Issue: 10, Page: 9899-9908
2012
- 163Citations
- 5,914Usage
- 216Captures
- 1Mentions
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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
- Citations163
- Citation Indexes160
- 160
- CrossRef59
- Patent Family Citations3
- 3
- Usage5,914
- Downloads5,637
- 5,637
- Abstract Views277
- Captures216
- Readers216
- 216
- Mentions1
- References1
- 1
Review Description
Mobile or SMS spam is a real and growing problem primarily due to the availability of very cheap bulk pre-pay SMS packages and the fact that SMS engenders higher response rates as it is a trusted and personal service. SMS spam filtering is a relatively new task which inherits many issues and solutions from email spam filtering. However it poses its own specific challenges. This paper motivates work on filtering SMS spam and reviews recent developments in SMS spam filtering. The paper also discusses the issues with data collection and availability for furthering research in this area, analyses a large corpus of SMS spam, and provides some initial benchmark results.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0957417412002977; http://dx.doi.org/10.1016/j.eswa.2012.02.053; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84859217714&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0957417412002977; https://api.elsevier.com/content/article/PII:S0957417412002977?httpAccept=text/xml; https://api.elsevier.com/content/article/PII:S0957417412002977?httpAccept=text/plain; https://arrow.tudublin.ie/scschcomart/17; https://arrow.tudublin.ie/cgi/viewcontent.cgi?article=1022&context=scschcomart
Elsevier BV
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