السلام اساس الاسلام

This article deals with a very important and basic feature of Islām on whose foundation the whole façade of Islām is erected, i. E., Peace. If we study the Quranic injunctions, the sayings of the Holy Prophet Muḥammad (r) and his kind actions i. E. His Sunnah, it becomes quite obvious that our topic of research is the top most concern of al-Sharī’ah, because peace is the foremost attribute of Islām. Islām means to prevail peace not only in the lives of the people in this world, but in the hereafter, too. In this research paper, the author has done his level best to prove that peace and solidarity play an important role in all the spheres and walks of life. Islām emphasizes it the most. Islamic teachings regarding peace include an individual’s life affairs, as well as the national and the international relations. We notice that all actions taken by the holy Prophet (r) meant to spread peace among the Muslims and the non-Muslims. The Holy Prophet (r) was explicitly declared as ‘Raḥmah li’l-‘Ālamīn’ (A mercy for all the worlds) by Almighty Allāh. We need to highlight and follow his sublime example to let the Muslims and the rest of the world know what Islām actually stands for; in a single word, it is just PEACE!

A Bayesian Network and Ontology Based Semantic Annotation Framework

The internet has become an attractive avenue for global e-business, e-learning, knowledge sharing, etc. Due to continuous increase in the volume of web content, however, it is not practically possible for a user to extract information by browsing and integrating data from a huge amount of web sources retrieved by the existing search engines. The semantic web technology aims to answer this and many other information extraction related issues by providing a suite of tools for integrating data from different sources. To take full advantage of semantic web, however, it is necessary to annotate existing web pages with semantics. Another difficulty that logically arises while accessing information over the web is the presence of unstructured, ungrammatical and incoherent format such as online advertisements, emails, reports etc. This thesis aims to answer few of the concern raised above and presents a semantic annotation framework that is capable of extracting relevant data from unstructured, ungrammatical and incoherent data sources and semantically annotating it. The semantic annotation framework is named BNOSA and it employs ontology and Bayesian network to perform semantic annotation. As the data is unstructured and ungrammatical, the framework exploits the use of context keywords along with domain knowledge to find the location of the data of interest in relevant data sources. Due to the variable size of information available on different web pages, it is often the case that the extracted data contains missing values for certain variables of interest or it may extract more than one value (conflicting values). It is desirable in such situations to predict the missing values and to resolve the conflicts by selecting the most relevant value. BNOSA employs Bayesian networks for missing value prediction and conflict resolution. The framework is extensible as it is capable of dynamically linking any problem domain given a pre-defined ontology and a corresponding Bayesian network. Experiments have been conducted to analyze the performance of BNOSA on several problem domains. The sets of corpora used in the experiments belong to selling-purchasing websites where product information is entered by ordinary web users in a structure free format. The results show that BNOSA performs better than the other recently proposed semantic annotation frameworks.