Enterprise Search Evaluation: Celebros Qwiser Salesperson V.4.0

2007 ◽  
Author(s):  
Susan Aldrich
Keyword(s):  
Enterprise Search

Enterprise Search Solution RFP Template

2006 ◽  
Author(s):  
Susan Aldrich
Keyword(s):  
Enterprise Search

Accomplishment and comparison of access control methods in enterprise search

2009 ◽  
Vol 29 (7) ◽  
pp. 2000-2002
Author(s):  
Qin CHEN ◽  
Huan YUAN ◽  
Jian-hua FENG
Keyword(s):  
Access Control ◽  
Control Methods ◽  
Enterprise Search

The CSIRO enterprise search test collection

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

scholarly journals Enterprise search: A state of the art

2019 ◽  
Vol 36 (2) ◽  
pp. 60-69
Author(s):  
Paul H Cleverley ◽  
Simon Burnett
Keyword(s):  
Oil And Gas ◽  
Search Task ◽  
State Of The Art ◽  
Feedback Loops ◽  
Future Directions ◽  
Business Outcomes ◽  
Technological Advances ◽  
Enterprise Search ◽  
Level Model ◽  
Systems Thinking Approach

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.

Semantic Search on Unstructured Data

2010 ◽  
Vol 6 (2) ◽  
pp. 17-35 ◽  
Author(s):  
Alex Kohn ◽  
François Bry ◽  
Alexander Manta
Keyword(s):  
Retrieval System ◽  
Pharmaceutical Research ◽  
Information Retrieval System ◽  
Semantic Search ◽  
Unstructured Data ◽  
Search Performance ◽  
Adaptive Search ◽  
Retrieval Performance ◽  
Enterprise Search ◽  
Existing Data

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.

scholarly journals Enterprise Search: Tough Stuff

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