4 research outputs found
Classifying the suras by their lexical semantics :an exploratory multivariate analysis approach to understanding the Qur'an
PhD ThesisThe Qur'an is at the heart of Islamic culture. Careful, well-informed interpretation of
it is fundamental both to the faith of millions of Muslims throughout the world, and
also to the non-Islamic world's understanding of their religion. There is a long and
venerable tradition of Qur'anic interpretation, and it has necessarily been based on
literary-historical methods for exegesis of hand-written and printed text.
Developments in electronic text representation and analysis since the second half of
the twentieth century now offer the opportunity to supplement traditional techniques
by applying the newly-emergent computational technology of exploratory
multivariate analysis to interpretation of the Qur'an. The general aim of the present
discussion is to take up that opportunity.
Specifically, the discussion develops and applies a methodology for discovering the
thematic structure of the Qur'an based on a fundamental idea in a range of
computationally oriented disciplines: that, with respect to some collection of texts, the
lexical frequency profiles of the individual texts are a good indicator of their semantic
content, and thus provide a reliable criterion for their conceptual categorization
relative to one another. This idea is applied to the discovery of thematic
interrelationships among the suras that constitute the Qur'an by abstracting lexical
frequency data from them and then analyzing that data using exploratory multivariate
methods in the hope that this will generate hypotheses about the thematic structure of
the Qur'an.
The discussion is in eight main parts. The first part introduces the discussion. The
second gives an overview of the structure and thematic content of the Qur'an and of
the tradition of Qur'anic scholarship devoted to its interpretation. The third part
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defines the research question to be addressed together with a methodology for doing
so. The fourth reviews the existing literature on the research question. The fifth
outlines general principles of data creation and applies them to creation of the data on
which the analysis of the Qur'an in this study is based. The sixth outlines general
principles of exploratory multivariate analysis, describes in detail the analytical
methods selected for use, and applies them to the data created in part five. The
seventh part interprets the results of the analyses conducted in part six with reference
to the existing results in Qur'anic interpretation described in part two. And, finally, the
eighth part draws conclusions relative to the research question and identifies
directions along which the work presented in this study can be developed
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Knowledge Based Information Retrieval: A Semiotic Approach
The overall objective of this study is to analyze the document retrieval process and the main information retrieval (IR) concepts from the point of view of semiotics and design retrieval mechanisms based on the findings of the semiotic analysis of the retrieval situation. Semiotics is a discipline which studies 'sign systems' and how signs are exchanged in communication. The semiotic view of IR interaction presented in this dissertation views document retrieval as a kind of human communication process taking place in a social and cultural realm.
The most important result of the semiotic model developed is the explication of the distinction between the knowledge production and transfer functions of document retrieval. The consequence of this finding is the conceptualization of the retrieval process as a dynamic and complex interplay between knowledge production and transfer tasks. It is hypothesised that, in the case of knowledge production, users of retrieval systems are interested in exploring new areas of the document collection which are not a priori known.
Two knowledge based systems are developed based on the Okapi probabilistic retrieval system. The purpose of the retrieval systems designed is posited, in general terms, as to suggest the users new search areas of potential interest. This is achieved by treating the Inspec thesaurus as a semantic network, and applying a heuristic spreading activation technique to generate clusters of terms linked in the Inspec thesaurus. Each cluster or batch of terms is conceived as representing a part of the general search area defined by the initial user search terms. The main design objective here is to enable the user to identify new search areas from the term information contained in the batches.
Two evaluation experiments were carried out with real users who had real information needs to test whether the batches were actually effective in defining search areas related to the original user queries and whether they were useful in pointing new areas which were potentially relevant to the users. A number of hypotheses related to the retrieval effectiveness of the knowledge based systems designed were also tested in the experiments. The main findings of the experiments indicate that:
• the batches were useful in representing search domains relevant to the users' queries
• in many cases the batches represented new ideas or new search domains to the users
• the knowledge based systems had similar retrieval effectiveness in terms of precision as the Okapi syste