Nurazzah Abd Rahman

Query expansion using thesaurus in improving Malay Hadith retrieval system

Thesaurus has become another valuable structure in any Information Retrieval system. It is a list of terms and concepts that provide a controlled vocabulary of words to use in document indexing, clustering, searching and retrieval. This paper present the results of expanding users query using Malay thesaurus in the process of searching Malay documents from Malay Hadith retrieval system. The results obtained shows that the retrieval effectiveness improves by four percent when thesaurus is employed in the process of retrieving Malay translated Hadith documents, compared to when single term queries are employed.

Efficient retrieval of Malay language documents using Latent Semantic Indexing

The main objectives of this research is to investigate whether by using Latent Semantic Indexing (LSI) will improve the retrieval effectiveness on Malay document, compared to by using exact term-matching technique. LSI is a mathematical approach that uses Singular Value Decomposition (SVD) to discover the important association of the relationship between terms and terms, terms and documents and documents and documents. Cosine similarity measurement is used to measure the similarity between the query word and terms as well as the documents. This research uses Malay Language Test Collection consisting of 210 Malay documents, queries, relevant judgment and Malay stemmer to stem Malay terms. Results and analyses show that, LSI retrieval method outperformed the exact term-matching technique despite the longer processing time it took during the indexing. The best result for retrieval effectiveness for Malay documents in this domain is achieved when k-dimension is 4 and the threshold value is 0.8, which is 80.2 percent.

A Parallel Latent Semantic Indexing (LSI) Algorithm for Malay Hadith Translated Document Retrieval

Latent Semantic Indexing (LSI) is one of the well-known searching techniques which match queries to documents in information retrieval applications. LSI has been proven to improve the retrieval performance, however, as the size of documents gets larger, current implementations are not fast enough to compute the result on a standard personal computer. In this paper, we proposed a new parallel LSI algorithm on standard personal computers with multi-core processors to improve the performance of retrieving relevant documents. The proposed parallel LSI was designed to automatically run the matrix computation on LSI algorithms as parallel threads using multi-core processors. The Fork-Join technique is applied to execute the parallel programs. We used the Malay Translated Hadith of Shahih Bukhari from Jilid 1 until Jilid 4 as the test collections. The total number of documents used is 2028 of text files. The processing time during the pre-processing phase of the documents for the proposed parallel LSI is measured and compared to the sequential LSI algorithm. Our results show that processing time for pre-processing tasks using our proposed parallel LSI system is faster than sequential system. Thus, our proposed parallel LSI algorithm has improved the searching time as compared to sequential LSI algorithm.

Hash join algorithms used in text-based information retrieval: Guidelines for users

Text-Based Information Retrieval (IR) is a field where the search in a large document is a basic concept. Concise queries are very fundamentals process in order to satisfy user’s need for information. One of the basic fundamental techniques in IR to implement queries is Hashing. Different types of hashing algorithms are used in IR. This paper discussed about guidelines for users who are implementing Hash join algorithm variations in their IR applications. Algorithms are varied based on its techniques involved in join operations. Three different variations of hash join algorithm, namely, XJoin algorithm, Hash Merge Join (HMJ) algorithm, and Early Hash Join (EHJ) algorithm are studied experimentally. Analysis on the results obtained is given. A user guideline based on three factors: overall execution time, response time and input/output operations performed are presented.

Malay document clustering using complete linkage clustering technique with Cosine Coefficient

Finding useful and relevant information is a very challenging task to the user. The retrieval system usually responded with a long listed documents which are not necessarily relevant to the users need. Document clustering is a special technique that can sort out the documents effectively so that documents in the same cluster are similar to each other and documents in different cluster are dissimilar to each other. This paper focuses on document clustering for Malay test collection. It consists of 2028 Malay translated Hadith documents from book Sahih Bukhari. This paper presents the results using Complete Linkage Clustering algorithm with Cosine Coefficient on Malay translated Hadith documents. The evaluation of the experiments uses Recall (R), Precision (P) and Effectiveness (E) measure. The experiments is conducted on 100 clusters, 50 clusters and 20 clusters. It shows that the smaller the size of clusters, Recall (R) will increase, but Precision (P) will decrease. Results for Effectiveness (E) measure compared to the non-clustered documents show that applying clustering algorithm will improved the effectiveness of searching process. For this experiment 20 clusters is rather effective compared to the others.

A Survey on Context-Aware InformationRetrieval Research

Most of the retrieved documents from the Information Retrieval (IR) System are irrelevant to the user because the IR cannot determine the user’s context. One of the main issues is that the relevancy of the retrieved documents is based on personal assessment that depends on the task to be done and its context. This paper provides the review of prior researches (2003–2016) and concludes the review by providing the summary of the research’s current trends, future direction and opportunity and defining the research gap. First, the findings show that in prior studies, there is no identification of contextual aspect has been done in optimizing the ranking function of the Malay IR. Second, in optimizing the ranking function, the integration process of context representation and document ranking must be done. This approach also has not been done yet in the development of Malay Document Retrieval. If it still stays in the current status, the Malay Document Retrieval system cannot be improved compared to the traditional languages of Context Aware IR System (English).

Enhancing Latent Semantic Analysis by Embedding Tagging Algorithm in Retrieving Malay Text Documents

Latent Semantic Analysis (LSA) is a mathematical approach that uses Singular Value Decomposition to discover the important association of the relationship between terms and terms, terms and documents and also documents and documents. LSA adopted cosine similarity measure to calculate the similarity between the query and terms as well as the documents. This approach seem to be efficient if each of the term only have single meaning and a meaning only represent by single term. Unfortunately, there are terms that have multiple meanings and a single meaning that represent by multiple terms. If these terms are treated as a single word, it will lead the search engine to retrieve the irrelevant documents. The irrelevant documents that been retrieved will affect the effectiveness of the search engine. This paper propose to enhance LSA by embedding tagging algorithm. To investigate the effectiveness of LSA using tagging algorithm in retrieving documents from the Malay corpus, seven experiments are conducted. The first experiment conducted to compare the time taken for extracting the normal term list and the tagged term list, total number of both lists and also the time taken for the creation of term document matrix. All other experiments record all the results of the retrieval system by using different dimension and threshold value. The retrieval result averagely shows F-measure enhancement of approximate to 3.60% by using LSA with tagging algorithm (LSAT) compared to retrieval result of LSA.

Identifying concept from English translated Quran

Ontology learning is a field of extracting ontological elements to form ontology. Identification of concepts is the main activities within ontology learning. Diverse methods can be used to find concepts. One of the methods is using collocation learning technique. The technique used statistical scores which to test the strength of the connection between terms. In English translated Quran, single term Allah has occurred more frequently. The highest occurrences make the term Allah as concept but ignore the multi terms that related terms to Allah. This paper proposed a method to extract concept. It is based on collocation of terms related to Allah. The collocation used Ngram method. The result shows that the collocation method is able to identify terms related to Allah to be as concepts.

Graph-based text representation for Malay translated hadith text

Text representation plays an important role in text classification. Commonly, text representation uses the term frequency technique. Hadith texts consist of two parts; they are the chain of narrators and the content. The term frequency technique is usually used for the content text representation. This research explains the text representation for chain of narrators in hadith texts. The chain of narrators was depicted using graph technique as text representation. A total of 18 hadith texts were used in representing chain of narrators as text representation. The narrators name and relationships between narrators extracted from hadith texts which produced 82 narrator names and 85 connections between narrators. The 82 names were used as nodes, while the 85 connections as the relationships. The text representation graph subsequently used in the hadith text classification research based on chain of narrators.

Exploring user spiritual experience with Islamic websites for elderly

Studies of the elderly have shown that the elderly may turn to spirituality and religion when they meet difficult life changing events and experience personal losses. Therefore, instilling hope, offering support and therapeutic interventions such as prayer, thought, morality, artistic expression or professional referrals through the means of ICT technology such as religious Web sites may lead to spiritual rejuvenation and healing. Internet has become a primary source of information about Islam for its Muslim followers and other people from different religious beliefs. There are thousands of Islamic Web sites on the Internet, however, majority of them were found low in user satisfaction. One of the reasons was because they failed to provide necessary spiritual experience to the users. Thus, this study was undertaken to explore user spiritual experience with the Islamic Web sites. We employed a user study with seven older participants to help us understand their spiritual experiences. We asked their experiences with two chosen Islamic Web sites and their own favourite Web sites. From the study, we learnt that user spiritual experience is very much affected by Islamic spiritual interfaces, trusted contents and the Web site usability.