Method of Semantic Refinement for Enterprise Search

Author(s):  
Alexey Pismak ◽  
Serge Klimenkov ◽  
Eugeny Tsopa ◽  
Alexandr Yarkeev ◽  
Vladimir Nikolaev ◽  
...  
Keyword(s):  
2009 ◽  
Vol 29 (7) ◽  
pp. 2000-2002
Author(s):  
Qin CHEN ◽  
Huan YUAN ◽  
Jian-hua FENG

2007 ◽  
Vol 41 (2) ◽  
pp. 42-45 ◽  
Author(s):  
Peter Bailey ◽  
Nick Craswell ◽  
Ian Soboroff ◽  
Arjen P. de Vries

2019 ◽  
Vol 36 (2) ◽  
pp. 60-69
Author(s):  
Paul H Cleverley ◽  
Simon Burnett

Enterprise search is changing. The explosion of information within organizations, technological advances and availability of free OpenSource machine learning libraries offer many possibilities. Eighteen informants from practice, academia, search technology vendors and large organizations (Oil and Gas, Governments, Pharmaceuticals, Aerospace and Retail) were interviewed to assess challenges and future directions. The findings confirmed the existence of the ‘Google Habitus’, technology propaganda and a need to transcend disciplines for a Systems thinking approach toward enterprise search. This encompasses information management, user search literacy, governance, learning feedback loops as well as technology. A novel four-level model for enterprise search use cases is presented, covering search as a utility, search as an answer machine, search task apps and a discovery engine. This could be used to reframe enterprise search perceptions, expanding possibilities and improving business outcomes.


Author(s):  
Alex Kohn ◽  
François Bry ◽  
Alexander Manta

Studies agree that searchers are often not satisfied with the performance of current enterprise search engines. As a consequence, more scientists worldwide are actively investigating new avenues for searching to improve retrieval performance. This paper contributes to YASA (Your Adaptive Search Agent), a fully implemented and thoroughly evaluated ontology-based information retrieval system for the enterprise. A salient particularity of YASA is that large parts of the ontology are automatically filled with facts by recycling and transforming existing data. YASA offers context-based personalization, faceted navigation, as well as semantic search capabilities. YASA has been deployed and evaluated in the pharmaceutical research department of Roche, Penzberg, and results show that already semantically simple ontologies suffice to considerably improve search performance.


Queue ◽  
2004 ◽  
Vol 2 (2) ◽  
pp. 36-46 ◽  
Author(s):  
Rajat Mukherjee ◽  
Jianchang Mao
Keyword(s):  

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