The need for information web-searching is needed by many users nowadays. They use the search engines to input their query or question and wait for the answer or best search results. As results to user query the search engines many times may be return irrelevant pages or not related to information need. This paper presents a proposed model to provide the user with efficient and effective result through search engine, based on modified chicken swarm algorithm and cosine similarity to eliminate and delete irrelevant pages(outliers) from the ranked list results, and to improve the results of the user's query . The proposed model is applied to Arabic dataset and use the ZAD corpus dataset for 27300 document. The experimental result shows that the proposed model improves the precision, recall, and accuracy. Thus the result produced by this method improves accuracy.
Search Result Enhancement For Arabic Datasets Using Modified Chicken Swarm
search result
dissimilar pattern
outlier
chicken algorithm
swarm
redundant
relevant
rank list
Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
Today the trend is to perform software development work via distributed geographical area among team
individual or even as an organization. However
due to the global market and international presence of many companies
there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space
time and organizational boundaries via information and communication technologies. A global virtual team relies on communication
collaboration
and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study
we investigated factors that affect global virtual teams’ performance
factors considered include cultural differences
language problems
time-zone differences
team size
technical problems
lack of trust
lack of sufficient training
and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand
team size is the lowest level of effect on global virtual teams’ performance. © 2005 - 2016 JATIT & LLS. All rights reserved.
(23)
