Title
Leveraging sources of collective wisdom on the web for discovering technology synergies
Abstract
One of the central tasks of R&D strategy and portfolio management at large technology companies and research institutions refers to the identification of technological synergies throughout the organization. These efforts are geared towards saving resources by consolidating scattered expertise, sharing best practices, and reusing available technologies across multiple product lines. In the past, this task has been done in a manual evaluation process by technical domain experts. While feasible, the major drawback of this approach is the enormous effort in terms of availability and time: For a structured and complete analysis every combination of any two technologies has to be rated explicitly. We present a novel approach that recommends technological synergies in an automated fashion, making use of abundant collective wisdom from the Web, both in pure textual form as well as classification ontologies. Our method has been deployed for practical support of the synergy evaluation process within our company. We have also conducted empirical evaluations based on randomly selected technology pairs so as to benchmark the accuracy of our approach, as compared to a group of general computer science technologists as well as a control group of domain experts.
Year
DOI
Venue
2009
10.1145/1571941.1572035
SIGIR
Keywords
Field
DocType
novel approach,large technology company,available technology,technology synergy,synergy evaluation process,manual evaluation process,collective wisdom,control group,technical domain expert,domain expert,leveraging source,empirical evaluation,technological synergy,text mining,web 2 0,semantic similarity,portfolio management,best practice
Drawback,Data mining,Subject-matter expert,Project portfolio management,Computer science,Knowledge management,Web 2.0,Ontology (information science),Semantic similarity,World Wide Web,Best practice,Information retrieval,Collective wisdom
Conference
Volume
ISSN
Citations 
406
1860-949X
1
PageRank 
References 
Authors
0.38
15
2
Name
Order
Citations
PageRank
Cai-Nicolas Ziegler1150783.74
Stefan Jung210.38