Purpose – The purposes of this study were to measure the relevance status of Index Islamicus, evaluate the semantic correlation between a query and documents and inquire the basis of its rank. Sorting the retrieved results from the most relevant to the least relevant is the common option of an information retrieval system. This sorting mechanism or relevance judgment is computed by measuring closeness of query with its documents. Design/methodology/approach – Forming up 100 queries on Islamic History and Civilizations, with two indexing elements (keyword and concept), a laboratory experiment was generated on its first ten items of the rank. Throughout an experimental research design, the relevance status value formula was used to measure system-computed rank and compare it with mean average precision. Findings – The results showed that the average status value of Index Islamicus’s ranking on relevance criterion was 18 per cent effective in terms of retrieving precise documents. Despite the main focus of this study being only on one subject domain and the items calculated were only 1,000, this small percentage of its ranking mechanism proved that semantic correlations between queries with subject domain did not achieve the satisfactory level. Research limitations/implications – Implication of this study could be a guideline for further research on ranking mechanism of other search engines because the limitation of this study was Index Islamicus being the only database, which was the focus of this study. Practical implications – Throughout this study, Index Islamicus would be benefited knowing the status of its ranking mechanism as well as other databases can make further research on their own ranking method following this study. Social implications – Researchers and vendors of online databases can ensure their users a true platform of search engine with a proper ranking list. Originality/value – Relevance status value model for Index Islamicus on Islamic History and Civilization that allows the system to rank documents according to the match between document and query and gives the idea of a better index. The model improves the system’s ranking mechanism, and promotes the use of semantic relationships. This research promotes the computation of relevance status value by domain for capturing subject-specific relevance criteria and semantic relationships.

Every year the library of IIUM subscribes to quite a number of online databases with huge expenses but the utilization of these databases is countable. 10 out of 53 subscriptions have been terminated by 2015 to save the cost go in vain. The purpose of this paper is to develop a model based on the ISB elements to identify the reason behind this low usage and to increase the usage of online databases in the future. It has undertaken a quantitative approach to identify the elements of ISB among undergraduate (UG) students. The primary data has been collected through questionnaires based on the variables identified in the objective. There are 118 samples participating in this research and the proposed model has been adapted from Savolainen and Wilson. Psychological perception, searching strategies and the information resources have been considered as the independent variable and measured the usage of the online database among UG students as the dependent variable. The results have shown that there are seven elements which have an influence on the usage of the online database among IIUM UG students. Despite the limited number of samples and a specific group of students, the proposed model can enhance the usage of online database system subscribed to by IIUM library and a search engine can be developed to get the usage increased. In that sense, it is recommended to involve more participants from the different levels of students and users to get diverse elements of ISB. However, the paper contributes to bridging the gap between the online database usage and the users, believed to have an effective outcome for online database subscription. It is hoped that the proposed model would significantly fill this gap and help the library to increase the number of users for their expensive databases.

Thematic interpretations of al-Qur’ān (TIaQ) has a sensitivity due to the interrelation of Qur’ānic verses/ verse with each other. The purpose of this research was to extract the online Qur’ānic search engines (OQSE) and investigate the existing thematic interpretations of al-Qur’ān (TIaQ) based on the alignment with their relevant verses. The OQSEs provide the list of themes and the aligned verses theme and the aligned rhyme in their websites. The ambiguous thematic search engines have the possibility to mislead the user by retrieving nonaligned verses against a certain subject/theme (query) or the user may not fully understand the interpretations due to the incomplete results. The extracting of themes/topic and the aligned verses have been conducted using Cranfield’s Index Device method. Then a two-round Delphi method has been applied to justify the existing themes and the aligned verses by 20 experts of Qur’ānic discipline. There are 240 themes and 400 verses have been extracted and categorized into 40 thematic groups (TG). The experts’ justification through Delphi method has revealed that the accuracy of ordinated thematic groups in OQSE is 40% (16/40) only and the accuracy of the ordination of the themes and the verses achieved 35.41% (85/240). Despite the significant outcome of this research, the limitation recommends that further research should be conducted extracting more themes and aligned verses from OQSEs. Instead of 20 experts in Delphi, future research can concentrate on a big number of experts to investigate all the thematic verses of entire Qur’ān. Keywords—Delphi; Thematic interpretation; Tafseer; Qur’ānic search, Qur’anic theme

Social media is an open platform to communicate, share and exchange information freely. This uncontrolled exchanged information carries out both negative and positive impacts in others’ lives. In this regard, this study aims to identify ethical issues on this information in line with Ibn Khaldun’s ethical considerations. Out of many other social networking sites, Twitter has been identified as one of the most popular microblogging social networking platforms. Using a simple algorithm in R programming and 43 keywords based on Ibn Khaldun’s thoughts, 1075 public tweets have been extracted from Twitter as a sample of ethical issues. The sentiment analysis in Parallel Dots was performed on the collected tweets, and it was discovered that 700 of the tweets are positive statements, 229 are neutral statements, and 146 are negative statements. Having done the validation process on these sentiments, the study proposed these identified ethical issues from tweets as a domain in developing ontology relationships with Ibn Khaldun’s thoughts. In this process, further study can be carried on with wider data from various sources beyond the limitation of this study. Thus, a semantic database could serve as a guideline for SNS ethical issues based on Ibn Khaldun’s thoughts.

The research is based on studies on semantics used in GPS guided mobile navigation applications in particular for blind pedestrians. The scope is in information of words or narrative use in guiding them and how to improve the effectiveness in the semantics via machines learning. These are tested in this research. The long term goal is to create a mobile technology, self-contained system that allows blind users to navigate through unfamiliar environments