Volume 4, Issue 7, 2014

By | August 11, 2018

 Text Summarization as Feature Selection for Arabic Text Classification

Eman Al-Thwaib
Computer Information Systems Department, University of Jordan, Amman, Jordan.

Abstarct- Text classification (TC) or text categorization task is assigning a document to one or more predefined classes or categories. A common problem in TC is the high number of terms or features in document(s) to be classified (the curse of dimensionality). This problem can be solved by selecting the most important terms. In this study, an automatic text summarization is used for feature selection. Since text summarization is based on identifying the set of sentences that are most important for the overall understanding of document(s). We address the effectiveness of using summarization techniques on text classification.
Another feature selection technique is used, which is Term Frequency (TF) on the same but full-text data set, i.e., before summarization. Support Vector Machine is used to classify our Arabic data set. The classifier performance is evaluated in terms of classification accuracy, precision, recall, and the execution time. Finally, a comparison is held between the results of classifying full documents and summarized documents.

Keywords-Text Categorization; Text Summarization; Support Vector Machine; Feature Selection.

A Local Time Calculating Courseware for Geography Students: Does it assist Teachers?

Nor Hasbiah Ubaidullah, Jamilah Hamid, Aslina Saad, Sairabanu Omar Khan
Computing Department, Universiti Pendidikan Sultan Idris, 35000 Tg. Malim, Perak, Malaysia.

In learning geography, most students have problems in a particular topic, which deals with the calculation of the local time based on a given longitude. This problem is further compounded when some of the teachers lack the necessary learning aids to help solve the problem. Against this backdrop, the authors carried out a study to examine prevailing problems in the learning of this particular topic. A qualitative research method was used involving a semi-structured interview. Four teachers (who were selected from a secondary school in Perak, Malaysia) were recruited as the interviewees. Findings of the research showed that existing teaching approach was ineffective as calculating the required local time was tedious. Moreover, the interviewees professed a strong need for a new approach, which could ease the calculating process. Together, these two important findings underscore the imperative to introduce a new teaching approach, preferably aided by a novel application, which can help geography teachers explain the calculation process more effectively. In this paper, the authors propose an instructional design model for the intended application to guide the development of such a learning too.

Keywords: local time; calculating courseware; geography students; instructional design model.

Intelligent Emergency Message Broadcasting in VANET Using PSO

Ghassan Samara, Department of Computer Science, Zarqa University, Zarqa, Jordan.
Tareq Alhmiedat, Department of Information Technology, Tabuk University, Tabuk, Saudi Arabia.

Abstract— The new type of Mobile Ad hoc Network which is called Vehicular Ad hoc Networks (VANET) created a fertile environment for research.
In this research, a protocol Particle Swarm Optimization Contention Based Broadcast (PCBB) is proposed, for fast and effective dissemination of emergency messages within a geographical area to distribute the emergency message and achieve the safety system, this research will help the VANET system to achieve its safety goals in intelligent and
efficient way.

Keywords- PSO; VANET; Message Broadcasting; Emergency System; Safety System.

 

 

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