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European Journal of Scientific ResearchISSN 1450-216X Vol.37 No.1 (2009), pp.36-40

© EuroJournals Publishing, Inc. 2009

http://www.eurojournals.com/ejsr.htm

Dialogue-based Visualization for Quranic Text

Aida Mustapha

Faculty of Computer Science and Information Technology

University Putra Malaysia, 43400 UPM Serdang, Malaysia

E-mail: [email protected]: +603-8946-6554; Fax: +603-8946-6577

Abstract

Visualization is a human cognitive activity and is not something that a computerdoes. A good visualization for Quranic text enables us to communicate the content with

clarity, precision, and efficiency. Being a large information source, a visualization systemfor Quranic text is required. This paper proposes AQILAH, dialogue-based informationvisualization for Quranic text. AQILAH facilitates the interaction and rearrange the content

based on need-to-know basis, as opposed to sequential order as in recitals.

Keywords: Dialogue Systems, Information Visualization, Quranic Text

1. IntroductionInformation visualization is the formation of mental visual images, the act or process of interpreting in

visual terms. Information visualization combines aspects of imaging, graphics, scientific visualization,

human-computer and human-information interactions, as well as information technology (Robertson,Card, and Mackinlay, 1993). Basically it is a mapping from data representation to perceptualrepresentations that maximize human understanding. In knowledge management, visualization is a type

of internalization process (Marwick, 2001) that transformed the knowledge from explicit to tacit.

Explicit knowledge in Quranic texts are the verses (ayat ), while the tacit knowledge is the mentalunderstanding based on the users experience exploring the Quranic text.

The Quranic text consists of 114 chapters (surah) of varying lengths. Each surah also differs

from one another in terms of the number of verses (ayat ) (Shakir, 1983). Previous works on Quranictext mainly focus on retrieval techniques through class menus, topical and keywords, and stemming

and block-level link (Atiyah, 1996; Aljlay and Frieder, 2002; Noordin and Othman, 2006), while

visualization techniques focus on terms visualization (Ismail et al, 2007) using graphical or imaging

techniques like hyperbolic trees and dynamic queries, which are hierarchical or diagrammatic in nature(Hamzah, 2007). The main argument behind graphical representation is that visual format assists users

in interpreting the data or information in the form of understanding or mental images.

Nonetheless, there are two kinds of statements in verses of Quranic text. First are statementsthat provide a clear, concise indication of the idea underlying a particular passage or passages

(muhkamat ). For instance, verses those refer to the creation of man from “out of a drop of sperm”

deliver the literal meaning of biological origin of human beings. Second are allegorical or symbolicstatements (mutashabihat ) that are not entirely clear as they convey several meanings, while some

carry other literal indications, although such indication might not be intended. For instance, verses

those refer to God’s being such that He is being indefinable and infinite in time and space are far from

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Dialogue-based Visualization for Quranic Text 37

describing Him, but are only to imply what He is not: namely, not limited in either time or space, not

definable in terms of comparison, and not to be comprised within any category of human thought.

Because mutashabihat verses are being conveyed as generalized metaphors that are wellbeyond the comprehension of human perception, mapping the data representations in the form of

Quranic terms should be represented differently from visual images. This paper proposes a dialogue-

based visualization system for Quranic text, whereby knowledge queries are in the form of naturallanguage, while the responses drawn from the knowledge source of Quranic text are also in natural

language. The remainder of this paper introduces the dialogue-based Quranic visualization, theproposed architecture, the prototype implementation of the visualization system, followed byconclusions and some direction to future works.

2. Dialogue-based Quranic VisualizationThe main idea behind Quranic visualization is the huge amount of data encoded in the body text; hence

an independent verse (ayat ) on its own is virtually incomprehensible. Quranic verses are to beinterpreted as a whole, within the context of the chapters (surah) in order to maximize the

understanding. Because interpretation of Quranic texts is highly contextual according to the chapters, a

visualization system must be able to capture co-occurrences of concepts across the chapters in its

original textual form, rather than in graphical or diagrammatical forms. For instance, repetitivereferences to the origin of human being can be quoted in many varying formulations like “Was he not a

drop of sperm emitted (In lowly form)” in [75.37] and “Verily We created man from a drop of mingled

sperm” in [76:2].Although question-answering or information retrieval systems are able to elicit a specific

reference in answer to a query, the nature of knowledge organization in Quranic texts made the user

learning model confined to the scope of the query. Dialogue-based systems, on the other hand, respondto user queries in a more elaborated fashion through series of verses related to the queries. Hence, a

dialogue-based visualization is more akin to formation of mental model as captured through

conversation with a human preacher. A dialogue-based visualization system advances theinternalization process through construction and reconstruction of user mental models until all

knowledge and relationships within the Quranic text is perceived by the users in its simplest form,which is in natural language.

A hypothetical scenario is when a PhD student is asked on the research he is working on. Theexplanation would start from a single broad answer (i.e., Artificial Intelligence) and only further

questions will lead to more detailed answers (i.e., to improve the efficiency of algorithm X ). It is very

rare, unless the opposing conversation participant is working in the same field, that a direct answer isobtained. Basing on the same ground, when a human preacher is asked on the biological origin of

human, it is very rare to receive a response in the form of specific reference to a particular verse, but

rather in the form of big conceptual picture with reference to many verses. In the essence, conversationdialogues encourage elaboration of concepts in a series of utterances rather than in a form of

hierarchical relationships.

3. Prototype of AqilahThe proposed dialogue-based visualization system is implemented as a prototype called AQILAH,based on the learnable conversational agent framework (Mustapha and Abu Bakar, 2005). Since the

architecture is reusable, the focus in this prototype development is the knowledge base preparation.

Nonetheless, the preparation must adhere to two important characteristics in dialogue conversations.One, the basic unit in a dialogue is in the form of sentence or utterance. Two, dialogue utterances are

produced in turns by two speakers; hence one speaker may produce more than one utterance. Figure 1

shows the general architecture in AQILAH.

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Dialogue-based Visualization for Quranic Text 39

Due to the nature of dialogue utterances, the Quranic texts are segmented into singular verses

that can be manipulated as individual dialogue utterances, which in turn, may be used on its own or in

a series of utterances in case of multiple utterance in a turn. There are three knowledge bases involvedin the process of preparing verses into response utterances, known as the Master, the Associate, and the

Random knowledge base.

The knowledge bases are organized in the form of input pattern and response templates. In theMaster knowledge base, pattern is the keyword to match with user inputs and the response templates

are in the form of references to verses. While patterns are indexed according to chapter numbers,singular utterances are indexed according to Quranic reference citation, for instance [8:73] refers toverse number 73 in chapter 8 of The Accessions. The wildcard ontology is designed as a flat file based

on the required architecture (Mustapha and Abu Bakar, 2005).

3.2. Associative and Random Base

The Associate knowledge base is required to store the associative lexicons, or words with similar

meanings. However, the design is not the same with thesaurus or dictionaries, whereby the contents aremeaning-bearing words in English (i.e., big vs. enormous). This associative base stores Islamic terms

of similar meaning like an Arabic word “nutfah”, which literary means “minute quantity of liquid” but

scientifically referred as “sperms”. The word of similar meaning serves as secondary knowledge basewhose function is to replace the non-existing keyword with the similar words and return to search in

the Master with the new keyword.

The Random knowledge base, on the other hand contains random responses to return to user

when search for patterns have been exhausted. The main idea is diversion by pointing to a new verse asa way to change current topic, hence admitting failure to match a response in a more natural way. It is

particularly important to maintain a high probability of success in returning a response while keeping

the conversation going.

4. Conclusions and Future Works

This paper began by showing that a dialogue system can be a good visualizing tool to navigating andlearning Quranic text, with interaction mechanism being the closest to a human preacher. This is

because Quranic text is a huge body of corpus and learning is usually not in sequential order as recitals.The information need is usually less specific and more general with hope to find the best explanation

for the knowledge quest. We then presented AQILAH, and further detailed the knowledge base for

AQILAH. Nonetheless, we would like to highlight some implications of using Quranic text as theknowledge source.

One is that, the source of Quranic text comes in written style thus resulting in rigid dialogues

utterances because the visualization system converses in the manner as provided by the source text.

However, given the fact that the knowledge from Quranic text should be treated earnestly, theauthoritative style of dialogue utterances is therefore suitable for this type of application. Second, the

chapter-length surah is hard to be subdivided into series of “turns” as a single-utterance style in

dialogue systems in effort to preserve the meaning and context. To resolve this, we adopted theQuranic text at face value. We used individual verse (ayat ) as a single utterance, therefore allowing

multiple references to a specific ayat because a particular ayat may be referred by different surah and it

may also appear more than once in the same surah.This research is hoped to pursue in two directions. The first is to explore into a probabilistic

corpus modeling based on the ground that most verses are repetitious in multiple places. We hope to

capture the probabilities for each verse and in turns collate the duplications to be considered as the bestreturn response during a particular session of so-called dialogue-based preaching. The next direction is

to incorporate an ontology (Yusof et al, 2009) that focuses on the structure of content so mapping from

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40 Aida Mustapha

the knowledge base to the pattern response templates can be improved. We hope to provide

comprehensive source for the dialogue-based Quranic visualization system.

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