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An Intelligent Hypertext System

Hu, Michael Junke; (1994) An Intelligent Hypertext System. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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This thesis investigates the applications of machine intelligence in information generation, organization, manipulation, search and retrieval. In order to alleviate and solve some problems in the present information retrieval (IR) community, and to increase the efficiency and effectiveness of information systems, a new data structure is proposed in the thesis. The conceptual index is external to the collection of information components (documents). It integrates the conventional global index with a special semantic network. As a result, a much richer set of concepts, as well as the relationships between concepts, can be represented in the data structure. It is shown in the thesis that such a data structure is more suitable for sophisticated IR environments such as hypertext, and could make automatic information generation, self-adjustment and evolvement, inferencing and reasoning possible. Based on the conceptual index, a soft-link hypertext model is developed and investigated. The soft-link hypertext model covers the Boolean search model, the probability model, the traditional hard-link hypertext model and the soft-link hypertext in one infrastructure. Its main features include automatic generation of the conceptual index, self-adjustment and evolvement, user-centered services for information retrieval and applications of machine intelligence in all aspects of the model. The soft-link hypertext model, including its state-space and all operations occurring in the space, is fully presented and evaluated in the thesis. It is implemented in a soft-link hypertext system called the Enhanced SuperBook and assessed in several small-scale controlled IR experiments. Its strengths, weakness, similarity with, and difference from other information models and systems are also studied in depth. Based on such an investigation, the thesis concludes that many aspects of information retrieval should benefit from the extensive application of the machine intelligence. Automation in information generation, organization, self-adjustment and evolvement, and assistance for information retrieval can not only increase the efficiency and effectiveness of the information systems, but also represents the essence of, and should have great impact on, future generations of IR systems.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: An Intelligent Hypertext System
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Thesis digitised by ProQuest.
URI: https://discovery.ucl.ac.uk/id/eprint/10102881
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