Ain Shams University, Faculty of Computer and Information Science
International Journal of Intelligent Computing and Information Sciences
1687-109X
18
1
2018
01
01
An Efficient Partitioning Technique in SpatialHadoop
1
13
15893
10.21608/ijicis.2018.15893
EN
Ahmed
Ahmed_Elashry@fci.kfs.edu.eg
Information System Department,
Faculty of Computers and Information,
Kafr El-Sheikh University, Egypt
Abdulaziz
Shehab
Information Technology Department, Faculty of Computers and Information,
Mansoura University, Egypt
Alaa
Riad
Information System Department,
Faculty of Computers and Information,
Mansoura University, Egypt
Ahmed
Aboul-fotouh
Information Technology Department, Faculty of Computers and Information,
Mansoura University, Egypt
Journal Article
2018
10
04
SpatialHadoop is a Hadoop framework supporting spatial information handling in light of MapReduce programming worldview. A huge number of studies leads to that SpatialHadoop outperforms the traditional Hadoop in both overseeing and handling spatial data operations. Indexing at SpatialHadoop makes it better than Hadoop. However, the design of a proficient and powerful indexing technique is stay as a major challenge. This paper presents a novel partitioning technique in SpatialHadoop. It has a better performance compared to other partitioning techniques. The proposed technique performance has been studied in several cases utilizing a real datasets on a spatial range and k-Nearest-Neighbour (kNN) queries. The experimental results have demonstrated the efficiency of the proposed technique.
https://ijicis.journals.ekb.eg/article_15893_08f8e7b5bcdd6c442de907a168913678.pdf
Ain Shams University, Faculty of Computer and Information Science
International Journal of Intelligent Computing and Information Sciences
1687-109X
18
1
2018
01
01
SEARCHSENSE: A SEMANTIC META SEARCH ENGINE
15
25
15907
10.21608/ijicis.2018.15907
EN
Maged
El-Sayed
Department of Information Systems and Computers, Faculty of Commerce, Alexandria University,
Alexandria, Egypt
Journal Article
2018
10
04
Despite the recent advancements in information retrieval research and in online search engines, satisfying the needs of search engines users remains largely challenging. This is due to many reasons including the size and richness of information available over the internet and the semantic gap between the intention of search engine user and how search engines understand that intention. <br /> This article highlights the main reasons for ineffective web searches and sheds the lights on the status of ongoing research stream, the SearchSense project, which focuses on improving the effectiveness of search engines in satisfying users’ needs. The research has been carried out through multiple projects that were implemented over several years with main overall focus on designing an effective semantic search engine. SearchSense employs the semantic technology to bridge the gap between search engines and their users and to provide a better presentation of web search results. SearchSense could be used as a Meta Semantic Search Engineontop of regular search engine or could easily be incorporated in any information retrieval system.<br /> The article describes the overall framework of the solution and outlines its main components. Details on the technicalities of the solution components are presented in relevant articles. The article also provided a summary of the results of the experiments that have been conducted to test the effectiveness of the solution.
https://ijicis.journals.ekb.eg/article_15907_ff1b63d9667b7a460e5e6f75e7ea10f3.pdf
Ain Shams University, Faculty of Computer and Information Science
International Journal of Intelligent Computing and Information Sciences
1687-109X
18
1
2018
01
01
DETECTING AND RESOLVING AMBIGUITY APPROACH IN REQUIREMENT SPECIFICATION: IMPLEMENTATION, RESULTS AND EVALUATION
27
36
15909
10.21608/ijicis.2018.15909
EN
Somaia
Osama
Computer Science Department, Faculty of Computer and Information Science, Ain Shams University
Cairo, Egypt
Mostafa
Aref
Computer Science Department, Faculty of Computer and Information Science, Ain Shams University
Cairo, Egypt
Journal Article
2018
10
04
Requirements documentsare always written in natural language. At the point when a sentence can be understood diversely among various readersambiguity is happened [1]. In this paper, we illustrate an automated tool for detectingand resolvingambiguities thatcause a high risk of misunderstanding byseveralreaders and lead to confusion, waste of both effort and time and rework. Sentences in a natural language requirements specification document thathaveambiguity are initialdetected automatically from the text andambiguity type is determined. Sentences thatincludeambiguity are thenresolved automatically also by resolving algorithm based on a set of rules that we collected from training data. We implemented a tool for Detecting and Resolving Ambiguity (DARA), in order to clarifyand estimate our approach. The tool focuses on Lexical, Referential, Coordination, Scope and Vague ambiguity.We determine on the results of a collection of requirement specification documents to evaluatethe performance and utility of the approach.<br />
https://ijicis.journals.ekb.eg/article_15909_f00056431303fe37b49c06290f0095eb.pdf
Ain Shams University, Faculty of Computer and Information Science
International Journal of Intelligent Computing and Information Sciences
1687-109X
18
1
2018
01
01
Exploring and Measuring the Key Performance Indicators in Higher Education Institutions
37
47
15914
10.21608/ijicis.2018.15914
EN
Mohammed
Badawy
Dept. of Information Systems and Technology, Institute of Statistical Studies and Research (ISSR)
Cairo University 1, 2, Giza, Egypt
A
Abd El-Aziz
Dept. of Information System, College of Computer and Information Sciences,
Jouf University, Kingdom of Saudi Arabia
Heshan
Hefny
Vice-Dean of Institute of Statistical Studies and Research (ISSR), Cairo University, Giza, Egypt
Journal Article
2018
10
04
To enhance the quality of higher education institutions (HEIs), key performance indicators (KPIs) must be explored and measured. KPIs deems as a measurable value which explains the effectiveness of an institution and how it is achieving key objectives. Institutions use KPIs for ensuring that they are going on the right way or not. Many of the indicators for HEIs have been developed before, but the main question is how to choose the indicators that fit the institution for achieving goals and how to measure these indicators. This paper provides a model to explore and measure KPIs using text mining and feature extraction technique and measure indicators automatically rather than traditional methods of exploring based a questionnaire, we measure KPIs to know the impact of exploring these KPIs on the overall performance in HEIs. The data for the present study was collected by the Institute of Statistical Study and Research (ISSR) in Cairo University, and the impact of KPIs on the overall performance of the institution was evaluated. This study adopted pre-processing techniques and keyword extraction using text mining tool (RapidMiner) to conduct the research.
https://ijicis.journals.ekb.eg/article_15914_08224d33c2cf25908eb291d4f1bd20a2.pdf