An inner-enterprise knowledge recommender system

Lü, Zhen; Huang, George Q.; Jiang, Zuhua

doi:10.1016/j.eswa.2009.06.057

Cited by 35 publications

(14 citation statements)

References 29 publications

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“…Thus Zhen et al [9,10] proposed an information recommender system based on workflow which introduced factor of task relationships derived from workflow into its algorithm. Referral information is changed according to busy degree of designer.…”

Section: Information Overload Filteringmentioning

confidence: 99%

Multiple views system to support awareness for cooperative design

Chen

Zhao

et al. 2015

Computer-Aided Design

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Section: Information Overload Filteringmentioning

confidence: 99%

Multiple views system to support awareness for cooperative design

Chen

Zhao

et al. 2015

Computer-Aided Design

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“…Plu et al [13] describe using recommender techniques to suggest contacts in a corporate environment. More related to DocuBrowse, Zhen et al [20] focus on fact-oriented recommendations, such as experiences with a particular vendor or with a specific product.…”

Section: Enterprise-oriented Recommendationsmentioning

confidence: 99%

DocuBrowse

Girgensohn

Shipman

Chen

et al. 2010

Proceedings of the 15th International Conference on Intelligent User Interfaces

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Browsing and searching for documents in large, online enterprise document repositories are common activities. While internet search produces satisfying results for most user queries, enterprise search has not been as successful because of differences in document types and user requirements. To support users in finding the information they need in their online enterprise repository, we created Docu-Browse, a faceted document browsing and search system. Search results are presented within the user-created document hierarchy, showing only directories and documents matching selected facets and containing text query terms. In addition to file properties such as date and file size, automatically detected document types, or genres, serve as one of the search facets. Highlighting draws the user's attention to the most promising directories and documents while thumbnail images and automatically identified keyphrases help select appropriate documents. DocuBrowse utilizes document similarities, browsing histories, and recommender system techniques to suggest additional promising documents for the current facet and content filters.

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“…A domain ontology based on users' interest in a heterogeneous environment for personalizing recommendation can minimize repetitive and tedious retrieved information (Ge, Chen, Peng, & Li, 2012). The recommendation mechanism proposed in (Zhen, Huang, & Jiang, 2010) formalizes an ontology-based context model from both the user and knowledge side and performs a semantic matching between for a more proactive way of recommendation.…”

Section: Ontologies As Knowledge Management Tools In Enterprisesmentioning

confidence: 99%

Investigating contextual ontologies and document corpus characteristics for information access in engineering settings

Mehrpoor

Ahlers

Gulla

et al. 2017

Journal of Information Technology Case and Application Research

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Knowledge and information resources play a pivotal role in enterprises and are valuable for solution reuse and learning through information access. However, identifying relevant information from a rapidly growing number of unstructured resources is challenging for users. We discuss a personalized information access tool for professional workplaces based on the recommender systems to provide relevant documents for users in specific work contexts based on domain-specific ontologies. Our use case is a multidisciplinary engineering project building an energy-efficient vehicle. We provide an indepth analysis of document corpus characteristics of this real-life shared engineering workspace to understand the content and context of documents using information retrieval methods and semantic annotations. Upon this, we build a contextual ontology as our knowledge domain for the recommender system. We validate our ontology-based content matching approach by evaluating the level of retrievability and coverage of the ontology against the indexed document corpus through experiments on the corpus and ontology. Our results provide insight into engineers' document workspaces and show that even a simple domain ontology is able to match a majority of documents from a domain-oriented corpus. The findings support our approach of using ontology-based recommendation for domain-specific workspaces.

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An inner-enterprise knowledge recommender system

Cited by 35 publications

References 29 publications

Multiple views system to support awareness for cooperative design

Multiple views system to support awareness for cooperative design

DocuBrowse

Investigating contextual ontologies and document corpus characteristics for information access in engineering settings

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