Everything is Filed under 'File'

Ahlers, Dirk; Mehrpoor, Mahsa

doi:10.1145/2700171.2791046

Cited by 1 publication

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, rarely is the data situation that simple and there rather is a disjoint knowledge management. On the one side, there is the formal KBE system, and on the other side, documents just informally reside in a file system [11], [12], [13]. In this general case, an engineer will work with very heterogeneous data from many sources as well as utilise multiple tools such as CAx, KBE, document storage, desktop search, Web search, etc.…”

Section: Application Scenariomentioning

confidence: 99%

“…Therefore, the adaptation and personalisation of the system is based on semantic analysis and annotation of documents and the context of users, but is refined by the interaction of users with the system, using both explicit and implicit feedback. Because of the special type of documents that may include many binary documents that cannot be analysed with textbased retrieval methods, we also aim to use features of the filesystem [11] to compute similarity features. A challenge is to integrate these varied and partially sparse features into a consistent grouping and ranking of documents.…”

Section: Issues Of Personalisation In Professional Searchmentioning

confidence: 99%

See 1 more Smart Citation

Challenges for information access in multi-disciplinary product design and engineering settings

Ahlers

Mehrpoor

Kristensen

et al. 2015

2015 Tenth International Conference on Digital Information Management (ICDIM)

View full text Add to dashboard Cite

In any larger engineering setting, there is a huge number of documents that engineers and others need to use and be aware of in their daily work. To improve the handling of this amount of documents, we propose to view it under the angle of a new domain for professional search, thus incorporating search engine knowledge into the process. We examine the use of Information Retrieval (IR), Recommender Systems (RecSys), and Knowledge Management (KM) methods in the engineering domain of Knowledge-based Engineering (KBE). The KBE goal is to capture and reuse knowledge in product and process engineering with a systematic method. Based on previous work in professional search and enterprise search, we explore a combination of methods and aim to identify key issues in their application to KBE. We list detected challenges, discuss information needs and search tasks, then focus on issues to solve for a successful integration of the IR and KBE domain and give a system overview of our approach to build a search and recommendation tool to improve the daily informationseeking workflow of engineers in knowledge-intense disciplines. Our work contributes to bridging the gap between Information Retrieval and engineering support systems.

show abstract

Section: Application Scenariomentioning

confidence: 99%

Section: Issues Of Personalisation In Professional Searchmentioning

confidence: 99%