An expert recommendation system using concept-based relevance discernment

Yukawa, Toshihiro; Kasahara, Kaname; Kato, T.; Kita, Tomio

doi:10.1109/ictai.2001.974472

Cited by 17 publications

(14 citation statements)

References 2 publications

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“…In this sense, the literature presents some initiatives to provide access to the tacit knowledge. Among these initiatives, we can mention ReferralWeb (Kautz et al, 1997), ERS (Yukawa et al, 2002), TABUMA (Reichling et al, 2005), ICARE (Petry, 2007) and SmallBlue (Lin et al, 2008).…”

Section: Expert Recommender Systemsmentioning

confidence: 99%

“…ERS (Expert Recommender System) (Yukawa et al, 2002) uses information retrieval methods to return people and/or organizations with strong relevance to a keyword or document. It uses a document base to find experts with relevance taking into account the desired topic and the person.…”

Section: Expert Recommender Systemsmentioning

confidence: 99%

“…Just as ERS (Yukawa et al, 2002), TABU-MA (Reichling et al, 2005) is an expert recommender system that exploits the ability of documents reflecting interests of a user. A set of documents associated to the user's work is used to generate his profile.…”

Section: Expert Recommender Systemsmentioning

confidence: 99%

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Recommending knowledge in a knowledge based social network

Silva

Costa

Jucá

et al. 2011

jacr

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Abstract:The organizations aim to increase its competitiveness. In this context, they have been searching for new ways to improve their productivity, the quality of their products, and cost reduction. To achieve these goals, it is essential to use the collaborators' potentials and the relationship among them to find and share tacit knowledge. Since tacit knowledge is stored in people's mind, it is hard to be formalized and documented. Facing this difficulty, identifying and recommending persons who retain the needed knowledge might be a good option. This work presents the Specialist Recommender System (SWEETS) and its application into the a.m.i.g.o.s. environment, a social network platform for knowledge management. The SWEETS system uses folksonomy to extract a lightweight ontology, which is essential to effectively identify people's skills. This lightweight ontology is based by tags (concepts) relating them to items (instances), and its co-occurrences. In addition, such ontology is domain independent, which is a contribution of this work. Applying the SWEETS system into the a.m.i.g.o.s. environment we are looking for minimizing the communication problem in the corporation, providing an improvement on knowledge sharing. Therefore, a better usage of the collaborators knowledge may be expected.

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Section: Expert Recommender Systemsmentioning

confidence: 99%

Section: Expert Recommender Systemsmentioning

confidence: 99%

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Recommending knowledge in a knowledge based social network

Silva

Costa

Jucá

et al. 2011

jacr

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“…For a specific category, the list of information about experts is provided to users. In order to ease the burden of browsing categories one by one, the list is provided to users actively based on their needs [14][15][16][17]. Then they can choose the expert from the list for help manually.…”

Section: Introductionmentioning

confidence: 99%

An Approach to the Match between Experts and Users in a Fuzzy Linguistic Environment

Yuan

2016

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Knowledge management systems are widely used to manage the knowledge in organizations. Consulting experts is an effective way to utilize tacit knowledge. The paper aims to optimize the match between users and experts to improve the efficiency of tacit knowledge-sharing. Firstly, expertise, trust and feedback are defined to characterize the preference of users for experts. Meanwhile, factors including trust, relationship and knowledge distance are defined to characterize the preference of experts for users. Then, a new method for the measurement of satisfaction based on the principle of axiomatic design is proposed. Afterwards, in order to maximize the satisfaction of both experts and users, the optimization model is constructed and the optimal solution is shown in the matching results. The evaluation results show the approach is feasible and performs well. The approach provides new insights for research on tacit knowledge-sharing. It can be applied as a tool to match experts with users in the development of knowledge management systems. The fuzzy linguistic method facilitates the expression of opinions, and as a result, the users-system interaction is improved.

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“…Although machine-readable dictionaries [3] are commonly used for this purpose, such dictionaries generally consist of words for daily use rather than technical terms used in specialized fields. The authors previously proposed the Concept-based Vector Space Model (CBVSM), which is able to capture the relationships between words used in target texts [14]. CBVSM provides a function that discerns the semantic similarity between words that appear in texts; this capability enables the system to process texts as if the technical terms are understood.…”

Section: The Ipn Function In Ibbsmentioning

confidence: 99%