Rasha Ismail

Rasha Ismail
Ain Shams University · Department of Information Systems

Professor

About

52
Publications
5,619
Reads
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149
Citations
Introduction
Dr. Rasha Ismail is an Associate Professor and vice dean for the postgraduate studies and research affairs in the Faculty of Computer and Information Sciences, Ain Shams University, Egypt. She received her Ph.D. from Ain Shams University in 2009 in Data Mining and Data Warehousing. She was the Director of the credit hours programs from 2013 to 2019. She has contributed in implementing of the current credit‐hour curriculum for the Undergraduate programs of Bioinformatics and Software Engineering

Publications

Publications (52)
Conference Paper
Protein analysis relevance in predicting protein function cannot be ignored. The ability to accurately classify proteins based on their sequences is important for the analysis process. Several feature extraction approaches are used to extract features from protein sequences, either 2D or 3D. The objective of this paper is to investigate the impact...
Article
Full-text available
Recently, deep learning models have emerged as promising methods for the diagnosis of different diseases. Cardiac disease is among the leading life-threatening diseases on a global scale. The aim of this paper is to propose an optimized Convolutional Neural Network (CNN) model for the classification of electrocardiogram (ECG) heartbeat data. The pr...
Chapter
Most recent applications such as sensor networks generate continuous data streams. Additional constraints are faced for efficient query processing of such data streams that have uncertain nature and require fast and timely processing. Traditional query processing techniques of static data process the whole data without partitioning them, which is n...
Article
Paroxysmal Atrial Fibrillation (PAF) is a special class of Atrial Fibrillation. Predicting PAF events from electrocardiogram (ECG) signal streams plays a vital role in generating real-time alerts for cardiac disorders. These alerts are extremely important to cardiologists in taking precautions to prevent their patients from having a stroke. In this...
Article
Full-text available
Liver cancer is one of the main causes of cancer-related deaths worldwide. Due to the extreme heterogeneity of this disease, its prognosis and management are still not yet standardized. Different treatment modalities are available. However, the patient’s response to each of them varies. Therefore, it is critical to establish a model to help physici...
Article
Many recent applications such as sensor networks generate continuous and time varying data streams that are often gathered from multiple data sources with some incompleteness and high dimensionality. Clustering such incomplete high dimensional streaming data faces four constraints which are 1) data incompleteness, 2) high dimensionality of data, 3)...
Article
Recent applications such as sensor networks generate continuous and dynamic data streams. Data streams are often gathered from multiple data sources with some incompleteness. Clustering such data is constrained by incompleteness of data, data distribution, and continuous nature of data streams. Ignoring missing values in incomplete data clustering,...
Conference Paper
Data mining techniques has shown great potential in biomedical and health care fields. The objective of this paper is to apply feature selection methods and data mining techniques to Egyptian liver cancer patients' data to predict their prognosis and extract important features that affect the patient's survivability. Genetic and Clinical data from...
Article
Full-text available
Cloud services have become an increasingly popular solution to provide different services to clients. One of the cloud services is database as a service (DBaaS), in which the service provider offers different resources such as software, hardware and network to the clients to be able to manage and administer the database. However, the data and the e...
Chapter
Full-text available
Recommendation system has witnessed a significant improvement with the introduction of data mining. Data mining services require accurate input data for their results to be meaningful, but privacy concerns may influence users to provide spurious information. In order to preserve the privacy of the client in data mining process, the issue of informa...
Article
Many modern applications of sensor networks and transaction analysis require real‐time processing of their stream data sets. These data streams vary continuously over time. Current stream processing approaches focus on only one of the two optimization perspectives, proposing optimization techniques for data streams processing regardless of the proc...
Conference Paper
Extracting knowledge from multimedia contents represents recently a big challenge. Organizing and analyzing multimedia collections requires specific tools for extracting knowledge from the contents to enable effective and efficient filtering, searching and retrieval. The use of knowledge models, such as Ontology, is gaining interest among multimedi...
Chapter
Stemming algorithms (stemmers) are used to convert the words to their root form (stem); this process is used in the pre-processing stage of the Information Retrieval Systems. The Stemmers affect the indexing time by reducing the size of index file and improving the performance of the retrieval process. There are several stemming algorithms; the mos...
Chapter
Cloud computing is considered as a technology paradigm shift as it enables users to save both development and deployment time. It also reduces the operational costs of using and maintaining systems and applications by using only what you want. Moreover, it allows usage of any resources with elasticity instead of predicting workloads. There are many...
Chapter
Many modern applications in several domains such as sensor networks, financial applications, web logs and click-streams operate on continuous, unbounded, rapid, time-varying streams of data elements. These applications present new challenges that are not addressed by traditional data management techniques. For the query processing of continuous dat...
Chapter
Web page classification has a crucial role in web mining. The massive amount of data available on the web makes it so important to build web page prediction models. We aim to build classification models that classify new instances depending on existing labeled web documents. This paper investigates the effect of the two powerful ensemble methods ca...
Article
Community detection has become a crucial task in social network mining. Detecting communities summarizes interactions between members for gaining deep understanding of interesting characteristics shared between members of the same community. In this research, we propose a novel community detection algorithm for the purpose of revealing and analyzin...
Article
Full-text available
Question answering communities (QAC) are nowadays becoming widely used due to the huge facilities and flow of information that it provides. These communities target is to share and exchange knowledge between users. Through asking and answering questions under large number of categories. Unfortunately there are a lot of issues existing that made kno...
Chapter
Large amounts of data are generated daily, according to the wide usage of social media websites and scientific data. These data need to be stored and analyzed to help decision makers but the traditional database concepts are insufficient. Data warehouse and OLAP are useful technologies in the storage and analysis of big data. Using MapReduce will h...
Article
Emergence of social networks facilitates individuals to communicate, share opinions and form communities. Organizations benefit from social networks in monitoring customers’ behavior. Social networks mining and analysis aims to segment customers and determine the most influential actors for viral marketing. In this article, we propose a novel socia...
Conference Paper
Community detection in real-world social networks has gained significant attention in the last decade. With the increase of rich attribute information associated with nodes, identifying meaningful communities becomes more challenging. In this paper, we propose a new algorithm for detecting communities that considers the structure of the network as...
Conference Paper
Multimedia enhances the applications with rich content. The uses of media tools moreover make communication more effective. Consequently, automatic image annotation and retrieval has recently occupied a large space in the multimedia research area. This paper presents a framework for automatic sport image annotation and content description for searc...
Article
Cloud computing is a promising computing model that provides a combination of parallel and distributed computing paradigms. It has the characteristics of on demand provisioning of a shared pool of configurable computing resources as a service. It provides a cost effective paradigm of computational, storage and database resources to users over the i...
Chapter
Cloud computing has become a powerful distributed computing mode. A Cloud system has a characteristics strength such as scalability and heterogeneity against the traditional distributed paradigm. These characteristics lead to increased numbers of clients needs to access and process data from multiple distributed resources over a cloud environment w...
Article
Web personalisation is the process of customising a website's content to users' specific needs. Next page prediction is one of the basic techniques needed for personalisation. In this paper, we present a framework for next page prediction that uses user-concept matrix clustering to integrate semantic information into web usage mining process for th...
Article
Over the years, several achievements on the improvement of web personalized searching based on user's interests, preferences and contextual information have been made, unfortunately, most of them are concerned with the static profile approach, preferences or weight values and not changed once the user preference profile is created and this might be...
Conference Paper
Most of the recent applications such as sensor networks applications, financial applications and click-streams applications generate continuous, rapid, unbounded and time varying datasets that are called data streams. In this paper we proposed a multiple queries optimization for data streams processing on cloud computing (MQODS) frameworks that eff...
Article
The World Wide Web is becoming the most important source to search for information or products. But the size and the unstructured nature of the available information makes the location of the right information a challenging task. Recommender systems and web usage mining techniques are two of the main methods used to overcome information overload. I...
Conference Paper
There are billions of web pages available on the Internet. Search Engines always have a challenge to find the best ranked list to the user’s query from those huge numbers of pages. A lot of search results that correspond to a user’s query are not relevant to the user’s needs. Most of the page ranking algorithms use Link-based ranking (web structure...
Conference Paper
Many recent applications in several domains such as sensor networks, financial applications, network monitoring and click-streams generate continuous, unbounded, rapid, time varying datasets which are called data streams. In this paper we propose the optimized and elastic query mesh (OEQM) framework for data streams processing based on cloud comput...
Article
Full-text available
There are billions of web pages available on the Internet. Search Engines always have a challenge to find the best ranked list to the user's query from those huge numbers of pages. A lot of search results that corresponding to a user's query are not relevant to the user need. Most of the page ranking algorithms use Link - based ranking (web structu...
Article
With the advances in communication and technologies, the World Wide Web is becoming an important and rich source for information. The amount and variety of information available makes customization and personalized recommendations of utter importance. In this paper, we present a framework for the next page prediction that exploits users' access his...
Article
Full-text available
Most of query optimizers choose a single query plan for processing all the data based on the average data statistics. But this plan is usually not efficient with the uncertain stream datasets of modern applications as network monitoring, sensor networks and financial applications; where these data have continuous variations over time. In this paper...
Article
Full-text available
Due to the existence of the 'database as a service' (DaaS) model on a cloud computing environment, several challenges have been made, such as query scheduling. Using an efficient query scheduler can improve the queries response time submitted from various clients in a DaaS model. Scheduling the queries in a cost aware way has an economic impact on...
Article
Full-text available
Most search engine systems mainly focusing on developing Western languages such as English so these search engine systems have a high performance on these languages but they don't have the same performance when they are used for Eastern languages such as Arabic. Furthermore, Arabic is a highly inflected language that has a complex morphological str...
Conference Paper
Full-text available
Stemming algorithms (stemmers) are used to convert the words to their root form (stem), this process is used in the pre-processing stage of the Information Retrieval Systems. The Stemmers affect the indexing time by reducing the size of index file and improving the performance of the retrieval process. There are several stemming algorithms, the mos...
Conference Paper
Full-text available
Workload management for concurrent queries is one of the challenging aspects of executing queries over the cloud computing environment. The core problem is to manage any unpredictable load imbalance with respect to varying resource capabilities and performances. Key challenges raised by this problem are how to increase control over the running reso...
Article
Recommender systems are means for web personalization and tailoring the browsing experience to the users' specific needs. There are two categories of recommender systems; memory-based and model-based systems. In this paper we propose a personalized recommender system for the next page prediction that is based on a hybrid model from both categories....
Conference Paper
Full-text available
Cloud computing is becoming increasingly popular as it enables users to save both development and deployment time. It also reduces the operational costs of using and maintaining the systems. Moreover, it allows the use of any resources with elasticity instead of predicting workload which may be not accurate, as the data warehousing environments can...
Conference Paper
Full-text available
Cloud computing is the latest evolution of computing. It provides services to numerous remote users with different requests. Managing the query workload in cloud environment is a challenge to satisfy the cloud users. Improving the overall performance and response time of the query execution can lead to users’ satisfaction. In this paper, we examine...
Conference Paper
The view maintenance issues are very important in the data warehouse process as its goal to make the data warehouse always consistent with its sources but it generates big challenges in the P2P environments. The materialized views maintenance problem take a lot of attention in distributed data warehouse but in the Peer to peer (P2P) systems there i...

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