Navigating the knowledge graph : automatically acquiring and utilising a domain model for intranet search
Search is becoming more interactive, and query logs are the commonly used resources to propose search suggestions. An alternative to exploiting query logs can be an extraction of a domain model based on actual documents. This is particularly promising when restricting search to an intranet or a Web...
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ndltd-bl.uk-oai-ethos.bl.uk-6530612016-08-04T04:09:44ZNavigating the knowledge graph : automatically acquiring and utilising a domain model for intranet searchAdindla, Suma2014Search is becoming more interactive, and query logs are the commonly used resources to propose search suggestions. An alternative to exploiting query logs can be an extraction of a domain model based on actual documents. This is particularly promising when restricting search to an intranet or a Web site where the size of the collection allows the application of full natural language parsing and where the documents can be expected to be virtually spam-free. Using a university Web site as an exemplar, we can automatically extract predicate-argument structures from documents to acquire a domain model. This domain model is a term association graph which can be employed to guide users in information finding. This can be done by locating a user query in the model and suggesting directly connected terms as query suggestions. Alternatively, one could apply various graph-based algorithms to the initial model with a purpose of identifying the best possible suggestions.004.678University of Essexhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.653061Electronic Thesis or Dissertation |
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004.678 Adindla, Suma Navigating the knowledge graph : automatically acquiring and utilising a domain model for intranet search |
description |
Search is becoming more interactive, and query logs are the commonly used resources to propose search suggestions. An alternative to exploiting query logs can be an extraction of a domain model based on actual documents. This is particularly promising when restricting search to an intranet or a Web site where the size of the collection allows the application of full natural language parsing and where the documents can be expected to be virtually spam-free. Using a university Web site as an exemplar, we can automatically extract predicate-argument structures from documents to acquire a domain model. This domain model is a term association graph which can be employed to guide users in information finding. This can be done by locating a user query in the model and suggesting directly connected terms as query suggestions. Alternatively, one could apply various graph-based algorithms to the initial model with a purpose of identifying the best possible suggestions. |
author |
Adindla, Suma |
author_facet |
Adindla, Suma |
author_sort |
Adindla, Suma |
title |
Navigating the knowledge graph : automatically acquiring and utilising a domain model for intranet search |
title_short |
Navigating the knowledge graph : automatically acquiring and utilising a domain model for intranet search |
title_full |
Navigating the knowledge graph : automatically acquiring and utilising a domain model for intranet search |
title_fullStr |
Navigating the knowledge graph : automatically acquiring and utilising a domain model for intranet search |
title_full_unstemmed |
Navigating the knowledge graph : automatically acquiring and utilising a domain model for intranet search |
title_sort |
navigating the knowledge graph : automatically acquiring and utilising a domain model for intranet search |
publisher |
University of Essex |
publishDate |
2014 |
url |
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.653061 |
work_keys_str_mv |
AT adindlasuma navigatingtheknowledgegraphautomaticallyacquiringandutilisingadomainmodelforintranetsearch |
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1718373009351245824 |