Hikmat Ullah Khan

Ontology Based Semantic Search in Holy Quran

Holy Quran, due to its unique style and allegorical nature, needs special attention about search and information retrieval issues. Many works have been done to accomplish keyword search from Holy Quran. The main problem in all these works is that these are either static or they does not provide us semantic search. In this paper, we propose that the concepts of ontology of semantic web can be applied for carrying out semantic search in Holy Quran. For this purpose, exploratory search have been done from semantic web field of knowledge. The sample domain ontology, based on living creatures including animals and birds mentioned in Holy Quran, has been developed in protégé ontology editor tool. SPARQL Queries have been run to depict the proper role of ontology. Then certain recommendation for the project of attaining semantic search from all domains and resultantly all text of Holy Quran has been proposed. These recommendations include model and framework including creation of Quranic WordNet, integration, merging and mapping of domain ontologies under the umbrella of upper ontology. This work can be extended to other Islamic knowledge sources like Hadith, Fiqh etc.

MIIB: A Metric to Identify Top Influential Bloggers in a Community.

Social networking has revolutionized the use of conventional web and has converted World Wide Web into the social web as users can generate their own content. This change has been possible due to social web platforms like forums, wikis, and blogs. Blogs are more commonly being used as a form of virtual communication to express an opinion about an event, product or experience and can reach a large audience. Users can influence others to buy a product, have certain political or social views, etc. Therefore, identifying the most influential bloggers has become very significant as this can help us in the fields of commerce, advertisement and product knowledge searching. Existing approaches consider some basic features, but lack to consider some other features like the importance of the blog on which the post has been created. This paper presents a new metric, MIIB (Metric for Identification of Influential Bloggers), based on various features of bloggers’ productivity and popularity. Productivity refers to bloggers’ blogging activity and popularity measures bloggers’ influence in the blogging community. The novel module of BlogRank depicts the importance of blog sites where bloggers create their posts. The MIIB has been evaluated against the standard model and existing metrics for finding the influential bloggers using dataset from the real-world blogosphere. The obtained results confirm that the MIIB is able to find the most influential bloggers in a more effective manner.

Finding the top influential bloggers based on productivity and popularity features

ABSTRACT A blog acts as a platform of virtual communication to share comments or views about products, events and social issues. Like other social web activities, blogging actions spread to a large number of people. Users influence others in many ways, such as buying a product, having a particular political or social opinion or initiating new activity. Finding the top influential bloggers is an active research domain as it helps us in various fields, such as online marketing, e-commerce, product search and e-advertisements. There exist various models to find the influential bloggers, but they consider limited features using non-modular approach. This paper proposes a new model, Popularity and Productivity Model (PPM), based on a modular approach to find the top influential bloggers. It consists of popularity and productivity modules which exploit various features. We discuss the role of each proposed and existing features and evaluate the proposed model against the standard baseline models using datasets from the real-world blogs. The analysis using standard performance evaluation measures verifies that both productivity and popularity modules play a vital role to find influential bloggers in blogging community in an effective manner.

Finding Resources from Middle of RDF Graph and at Sub-Query Level in Suffix Array Based RDF Indexing Using RDQL Queries

These Semantic Web promises to describe semantic information about its resources based on metadata concept. There are various schemes for querying metadata described with RDF and RDFS for effective query retrieval. Akioyoshi Matono et al. proposed indexing and query processing scheme for path based RDF query using suffix array. Sung Wan Kim proposed improved and efficient scheme for query processing based on longest common prefix concept. The results were shown using RDQL queries. There are two deficiencies, one that the proposed scheme deals with forward or backward queries and does not target resources in the middle of RDQL query. Second, various forms of RDQL queries especially based on sub-query concepts can not be answered from both the above cited schemes. In our proposed work, we have formally discussed proposed schemes to remove both these deficiencies and proposed respective solutions. The proposed work has been analyzed empirically and have found correct. The work will help to improve effectiveness in the search and retrieval of resources from suffix based RDF indexing using RDQL queries.

Comparative Analysis of Semantic Search Engines Base d on Requirement Space Pyramid

Semantic Web promises to add metadata to web content to make it understandable to computers. Search is the most widely used activity on web. Semantic search engines have already changed the way we search the data on web. Uren. V, Yuanguilei Uren et al., proposed requirement space pyramid arguing that iterative and exploratory search modes are important to the usability of search engines. It identified the types of semantic queries the users need to make, the issues concerning the search development and the problems intrinsic to semantic search in particular. We have extensively examined the semantic search engines and have done broad survey to analyse the semantic search engines. Comparative analysis of the semantic search engines have been done on the basis of factors cited in the pyramid. The research provides deep understanding of five main semantic search engines based on comparative analysis that may help for future work for semantic web in general and for semantic search engines in particular.

DS-Index: Ranking Authors Distinctively in an Academic Network

The impact and productivity of researchers are assessed using bibliometric parameters, such as the number of publications and citation analysis. A number of indices exist that use these parameters, but almost all of them overlook citation pattern of the researchers, which results in assigning the same index value to the two different authors with different citation patterns. In this paper, a new index called DS-index is proposed, which differentiates among the authors having even a very small change in the citation pattern of their publications. It uniquely identifies the different index values and thus the proper ranking order for authors. The index is applied to the self-developed large DBLP data set having publication data of over 50 years. The results compared with the existing indices using the standard performance evaluation measures confirm that the proposed index performs better by ranking the authors in a distinctive order.

Fighting adult illiteracy with the help of the environmental print material

Adult illiteracy is a major problem worldwide especially in developing countries. Adult Basic Education (ABE) programs working in this context are not very effective due to lack of motivation for the people who are not literate. The reason is inadequate learning content and content delivery methods. This situation calls for developing novel learning content and a learner-directed content delivery approach. This paper presents an exploratory study investigating the use of the Environmental Print Material (EPM) as learning content for the non-literate population of Pakistan. The EPM content is presented to the adult non-literate population in two ethnographic studies. The most frequently recognized content is selected and utilized as learning content in a Computer Assisted Learning (CAL) application. An empirical study is conducted upon two groups with 107 participants to compare the EPM-based learning content with Traditional Learning Content (TLC). As many as 54 participants participated in the experimental group (presented with EPM-based learning content), whereas 53 participants took part in the control group (presented with TLC content). The results reveal that the experimental group performed significantly better compared to the control group in recognition, pronunciation, and recall of the presented content. The meta-analysis of the results shows a large effect size of (1.05) with confidence interval in the range (0.798–1.315). The results claim that the EPM has potential to be considered as learning content in the ABE programs.

A Multilingual Datasets Repository of the Hadith Content

Knowledge extraction from unstructured data is a challenging research problem in research domain of Natural Language Processing (NLP). It requires complex NLP tasks like entity extraction and Information Extraction (IE), but one of the most challenging tasks is to extract all the required entities of data in the form of structured format so that data analysis can be applied. Our focus is to explain how the data is extracted in the form of datasets or conventional database so that further text and data analysis can be carried out. This paper presents a framework for Hadith data extraction from the Hadith authentic sources. Hadith is the collection of sayings of Holy Prophet Muhammad, who is the last holy prophet according to Islamic teachings. This paper discusses the preparation of the dataset repository and highlights issues in the relevant research domain. The research problem and their solutions of data extraction, pre-processing and data analysis are elaborated. The results have been evaluated using the standard performance evaluation measures. The dataset is available in multiple languages, multiple formats and is available free of cost for research purposes.

Evaluating Urdu to Arabic Machine Translation Tools

Machine translation is an active research domain in fields of artificial intelligence. The relevant literature presents a number of machine translation approaches for the translation of different languages. Urdu is the national language of Pakistan while Arabic is a major language in almost 20 different countries of the world comprising almost 450 million people. To the best of our knowledge, there is no published research work presenting any method on machine translation from Urdu to Arabic, however, some online machine translation systems like Google , Bing and Babylon provide Urdu to Arabic machine translation facility. In this paper, we compare the performance of online machine translation systems. The input in Urdu language is translated by the systems and the output in Arabic is compared with the ground truth data of Arabic reference sentences. The comparative analysis evaluates the systems by three performance evaluation measures: BLEU (BiLingual Evaluation Understudy), METEOR (Metric for Evaluation of Translation with Explicit ORdering) and NIST (National Institute of Standard and Technology) with the help of a standard corpus. The results show that Google translator is far better than Bing and Babylon translators. It outperforms, on the average, Babylon by 28.55% and Bing by 15.74%.

Modern Authentication Techniques in Smart Phones: Security and Usability Perspective

A smartphone has more advanced computing ability and connectivity than basic featured phones. Presently, we are moving from the Internet society to a mobile society where more and more access to the information is required. This has resulted in a mobile security which is no longer immanent, but imperative. Smartphone authentication has received substantial attention of the research community for the past several years because there have been modern developments beyond the classical PINs and passwords making user authentication more challenging. In this paper, we critically analyze the attacks and the vulnerabilities in smartphones’ authentication mechanisms. A comparative analysis of different authentication techniques along with the usage of the different authentication methods is discussed which lead the end-user towards choosing the most suitable and customizable authentication technique.