Predicting likelihood of legitimate data loss in email DLP
نویسندگان
چکیده
منابع مشابه
Predicting Email Response using Mined Data
Mailing lists are the primary medium of communication in open source projects. For some projects the sheer volume of emails on the mailing lists becomes unmanageable and messages may begin to be ignored. This can have a number of negative effects on an open source project. We present a way to predict who is most likely to respond to an email, thus providing the potential of giving mailing list ...
متن کاملmodeling loss data by phase-type distribution
بیمه گران همیشه بابت خسارات بیمه نامه های تحت پوشش خود نگران بوده و روش هایی را جستجو می کنند که بتوانند داده های خسارات گذشته را با هدف اتخاذ یک تصمیم بهینه مدل بندی نمایند. در این پژوهش توزیع های فیزتایپ در مدل بندی داده های خسارات معرفی شده که شامل استنباط آماری مربوطه و استفاده از الگوریتم em در برآورد پارامترهای توزیع است. در پایان امکان استفاده از این توزیع در مدل بندی داده های گروه بندی ...
Learning DLP from Uncertain Data
Description Logic Programs (DLP) is an expressive but tractable subset of OWL. In this paper, we study a rising but under-researched problem of learning DLP from uncertain data. Current research rarely explores the plentiful uncertain data populating the Semantic Web. We handle uncertain data in Inductive Logic Programming (ILP) framework by modifying the performance evaluation criteria. We ado...
متن کاملDlp
DLP (for Description Logic Prover) is a description logic system that contains a sound and complete rea-soner for an expressive description logic. DLP is an experimental system, in that it does not contain all the support facilities that one might like in a full description logic system. However, DLP does have an interface that allows the creation and examination of taxonomies of concepts. DLP ...
متن کاملBayesian and Iterative Maximum Likelihood Estimation of the Coefficients in Logistic Regression Analysis with Linked Data
This paper considers logistic regression analysis with linked data. It is shown that, in logistic regression analysis with linked data, a finite mixture of Bernoulli distributions can be used for modeling the response variables. We proposed an iterative maximum likelihood estimator for the regression coefficients that takes the matching probabilities into account. Next, the Bayesian counterpart...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Future Generation Computer Systems
سال: 2020
ISSN: 0167-739X
DOI: 10.1016/j.future.2019.11.004