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Register a new userتشفير وإخفاء المعلومات في الويب
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Aِl-Baath University أطروحة دكتوراه
Publication date
2016
fields
Mathematics
and research's language is
العربية
Created by
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تشفير وإخفاء المعلومات في الويب تستخدم تقانة المعلومات في تسيير معظم أعمالنا في الوقت الراهن مما يستوجب الانتباه لضرورة تأمين معلوماتنا الحساسة
No English abstract
References used
الناظر سائد 2005 التعمية وامن الشبكات درا شعاع للنشر سوريا
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We aimed to distinguish between them and the other research areas such as information retrieval and data mining. we tried to determine the general structure of such systems which form a part of larger systems that have a mission to answer user querie
s based on the extracted information. we reviewed the different types of these systems, used techniques with them and tried to define the current and future challenges and the consequent research problems.
Finally we tried to discuss the details of the various
implementations of these systems by explaining two platforms Gate and OpenCalais and comparing between their information
extraction systems and discuss the results.
Semantic Web is a new revolution in the world of the Web, where information and
data become viable for logical processing by computer programs. Where they are
transformed into meaningful data network. Although Semantic Web is considered the
future
of World Wide Web, the Arabic research and studies are still relatively rare in this
field. Therefore, this paper gives a reference study of Semantic Web and the different
methods to explore the knowledge and discover useful information from the vast amount
of data provided by the web. It gives a programming example like application of some of
these techniques provided by the Semantic Web and methods to discover the knowledge of
it. This simplified programming example provides services related to higher education
Syrian government, such as information about the Syrian public universities like the name
of the university (Syrian Virtual University, Tishreen, Aleppo, Damascus, and Al Baath),
address of the university, its web site, number of students and a summary of the university,
which helps intelligent agents to find those services dynamically.
The tasks of Rich Semantic Parsing, such as Abstract Meaning Representation (AMR), share similar goals with Information Extraction (IE) to convert natural language texts into structured semantic representations. To take advantage of such similarity,
we propose a novel AMR-guided framework for joint information extraction to discover entities, relations, and events with the help of a pre-trained AMR parser. Our framework consists of two novel components: 1) an AMR based semantic graph aggregator to let the candidate entity and event trigger nodes collect neighborhood information from AMR graph for passing message among related knowledge elements; 2) an AMR guided graph decoder to extract knowledge elements based on the order decided by the hierarchical structures in AMR. Experiments on multiple datasets have shown that the AMR graph encoder and decoder have provided significant gains and our approach has achieved new state-of-the-art performance on all IE subtasks.
We study in this research proposing and testing a new optimal algorithm in
performance and speed is suitable for caching of web objects with dynamic content
through studying the conventional classic algorithms that are common in caching web
pages
and studying how they can deal with caching web pages that have dynamic contents
due to their great importance and spread in web sites and what they cause of overload on
web servers to get a new algorithm that performs an optimal performance in dialing with
this type of web pages.
Part of a 2017 Master’s Degree in Web Science research, which includes the definition of marketing intelligence in an expanded theoretical study, the method of building an Internet-based system as a data source, processing methodology, and applied results.
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