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Topic Map and Its Application to Document Retrieval

Paper, was published by Haiyan Tian, Jiangning Wu, and Guangfei Yang at 2005-11-17

This paper mainly is about research on application of Topic Maps to information retrieval.

External Link: download paper

As computer and network technologies develop, information on line becomes flooded. Under this condition searching requested documents is really a difficult task. People are always seeking for an efficient searching tool and Topic Map is one of them. Topic Map is a new tool proposed by the International Organization for Standardization (ISO) to solve problems about knowledge representation and knowledge management. It has been widely used in many knowledge fields and in this paper we mainly make research on its application to information (document) retrieval. We firstly address some issues related to Topic Map: topic, association, occurrence as well as identity, facet and scope. By means of the current technologies for Topic Map developing, such as TMCL, TMQL, XML, SGML and so on, we propose a multi-layer Topic Map-based document retrieval model (TMDRM). TMRDM is based on Topic Map’s richly cross-linked structure and capabilities of topics used to group together objects that relate to a single abstract concept. This model helps people narrow the search scope step by step in order to facilitate them to proper documents.

Authors

Haiyan Tian

No contact information available. 

Signet_person

Haiyan is author of Topic Map and Its.. and A Multilayer.. .

Jiangning Wu

No contact information available. 

Signet_person

Jiangning is author of Topic Map and Its.. and A Multilayer.. .

Guangfei Yang

No contact information available. 

Signet_person

Guangfei is author of Topic Map and Its.. and A Multilayer.. .

glossary

TMQL

is associated with {{count}} items.

Signet_glossary

TMQL is the abbreviation for Topic Maps Query Language.

TMCL

is associated with {{count}} items.

Signet_glossary

TMCL is the abbreviation for Topic Maps Constraint Language.

XTM1

is associated with {{count}} items.

Signet_glossary

XTM1 is the short name for Topic Maps XML Syntax, Version 1.0.

 

Topic Maps is the only formal semantic model which is optimized for humans, not for computers. Applications and web portals based on Topic Maps are easy to use, without limitations for flexibility and creativity.

Benjamin-medium
Benjamin Bock
Ruby Topic Maps
practical-semantics.com
Topic Maps Lab auf der Cebit 2011
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Graduate from the Topic Maps Lab